diff --git "a/ssdlite_mobilenet_v2_fp16.xml" "b/ssdlite_mobilenet_v2_fp16.xml"
new file mode 100644--- /dev/null
+++ "b/ssdlite_mobilenet_v2_fp16.xml"
@@ -0,0 +1,14393 @@
+<?xml version="1.0"?>
+<net name="frozen_inference_graph" version="11">
+	<layers>
+		<layer id="0" name="image_tensor" type="Parameter" version="opset1">
+			<data shape="1,300,300,3" element_type="u8" />
+			<rt_info>
+				<attribute name="old_api_map_element_type" version="0" value="f32" />
+				<attribute name="old_api_map_order" version="0" value="0, 2, 3, 1" />
+			</rt_info>
+			<output>
+				<port id="0" precision="U8" names="image_tensor,image_tensor:0">
+					<dim>1</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+					<dim>3</dim>
+					<rt_info>
+						<attribute name="layout" version="0" layout="[N,H,W,C]" />
+					</rt_info>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="Preprocessor/mul/x_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 1, 1" offset="0" size="2" />
+			<output>
+				<port id="0" precision="FP16" names="Preprocessor/mul/x:0">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="Preprocessor/mul/x" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="Convert_2822" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="U8">
+					<dim>1</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="image_tensor/Transpose([0 3 1 2])/value2429333819" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="2" size="32" />
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="ToFloat" type="Transpose" version="opset1">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>300</dim>
+					<dim>300</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>300</dim>
+					<dim>300</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="Preprocessor/mul" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="Preprocessor/mul:0">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Preprocessor/sub/y_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 1, 1, 1" offset="34" size="2" />
+			<output>
+				<port id="0" precision="FP16" names="Preprocessor/sub/y:0">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="Preprocessor/sub/y" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="Preprocessor/sub" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="FeatureExtractor/MobilenetV2/MobilenetV2/input:0,Preprocessor/sub:0">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>300</dim>
+					<dim>300</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="Gather_3200_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 3, 3, 3" offset="36" size="1728" />
+			<rt_info>
+				<attribute name="preprocessing" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Gather_3200" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+				<attribute name="preprocessing" version="0" />
+			</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">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/mul_1" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_upper" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>300</dim>
+					<dim>300</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" names="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/mul_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/sub/_100__cf__103_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="1764" size="64" />
+			<output>
+				<port id="0" precision="FP16" names="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/sub/_100__cf__103:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/sub/_100__cf__103" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/add_1" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</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="FeatureExtractor/MobilenetV2/Conv/BatchNorm/batchnorm/add_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="FeatureExtractor/MobilenetV2/Conv/Relu6" type="Clamp" version="opset1">
+			<data min="0" max="6" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="FeatureExtractor/MobilenetV2/Conv/Relu6:0,FeatureExtractor/MobilenetV2/expanded_conv/input:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/mul_1_copy_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 1, 1, 3, 3" offset="1828" size="576" />
+			<output>
+				<port id="0" precision="FP16" names="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/depthwise_weights/read/_98__cf__101:0">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/mul_1_copy" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/depthwise" type="GroupConvolution" version="opset1">
+			<data strides="1, 1" pads_begin="0, 0" pads_end="0, 0" dilations="1, 1" auto_pad="same_upper" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</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" names="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/mul_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/sub/_97__cf__100_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="2404" size="64" />
+			<output>
+				<port id="0" precision="FP16" names="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/sub/_97__cf__100:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/sub/_97__cf__100" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/add_1" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</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="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/BatchNorm/batchnorm/add_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/Relu6" type="Clamp" version="opset1">
+			<data min="0" max="6" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="FeatureExtractor/MobilenetV2/expanded_conv/depthwise/Relu6:0,FeatureExtractor/MobilenetV2/expanded_conv/depthwise_output:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="FeatureExtractor/MobilenetV2/expanded_conv/project/weights/read/_95__cf__98_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="16, 32, 1, 1" offset="2468" size="1024" />
+			<output>
+				<port id="0" precision="FP16" names="FeatureExtractor/MobilenetV2/expanded_conv/project/weights/read/_95__cf__98:0">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="FeatureExtractor/MobilenetV2/expanded_conv/project/weights/read/_95__cf__98" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/mul_1" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_upper" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>150</dim>
+					<dim>150</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" names="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/mul_1:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>150</dim>
+					<dim>150</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/sub/_94__cf__97_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 16, 1, 1" offset="3492" size="32" />
+			<output>
+				<port id="0" precision="FP16" names="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/sub/_94__cf__97:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/sub/_94__cf__97" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="FeatureExtractor/MobilenetV2/expanded_conv/project/BatchNorm/batchnorm/add_1" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
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+	<rt_info>
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+		<Runtime_version value="2024.5.0-17210-c8747d74110-ea/add_support_ior" />
+		<conversion_parameters>
+			<input_model value="DIR/frozen_inference_graph.pb" />
+			<is_python_api_used value="True" />
+			<layout value="NHWC" />
+			<reverse_input_channels value="True" />
+			<tensorflow_object_detection_api_pipeline_config value="DIR/pipeline.config" />
+			<transformations_config value="DIR/ssd_v2_support.json" />
+		</conversion_parameters>
+		<legacy_frontend value="True" />
+	</rt_info>
+</net>