From 842f749650187441b17752f491c7e0adaa4b7691 Mon Sep 17 00:00:00 2001
From: tersekmatija <matija@luxonis.com>
Date: Fri, 6 Oct 2023 14:01:41 +0200
Subject: [PATCH 1/2] Add nanosam resnet18 image encoder

---
 .gitignore                                    |    1 +
 .../model.yml                                 |   40 +
 ...nosam_resnet18_image_encoder_1024x1024.xml | 4260 +++++++++++++++++
 3 files changed, 4301 insertions(+)
 create mode 100644 .gitignore
 create mode 100644 models/nanosam_resnet18_image_encoder_1024x1024/model.yml
 create mode 100644 models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml

diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..ef02941
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1 @@
+**/*.bin
diff --git a/models/nanosam_resnet18_image_encoder_1024x1024/model.yml b/models/nanosam_resnet18_image_encoder_1024x1024/model.yml
new file mode 100644
index 0000000..95f0f12
--- /dev/null
+++ b/models/nanosam_resnet18_image_encoder_1024x1024/model.yml
@@ -0,0 +1,40 @@
+description: ResNet18 image encoder for NanoSAM
+documentation: https://github.com/luxonis/depthai-model-zoo/tree/main/models/nanosam_resnet18_image_encoder_1024x1024
+files:
+- checksum: b752ae5aea32961a95957750c74c1c076953d3c392427303e2b60040a891b1f4c1d58f6deb8d7eee1c2d0246a323fc3a
+  name: FP16/nanosam_resnet18_image_encoder_1024x1024.xml
+  sha256: b9acf6c0314a48a52b2ca92b09b03f3159015ad0080f946e5f88da3d415953d0
+  size: 120264
+  source: https://github.com/luxonis/depthai-model-zoo/raw/main/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml
+- checksum: a8b93b905982c62043c3fff927a51094d3807ec4417f1326d9e9b73b3e384ed428c517f97881c4bcf77331629f8cecec
+  name: FP16/nanosam_resnet18_image_encoder_1024x1024.bin
+  sha256: 037a83d8b8666f6157d08e06417a0795a4f4a8c666b1b4c679321d2fcb6f323a
+  size: 31652102
+  source: https://robothub.fra1.cdn.digitaloceanspaces.com/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.bin
+framework: dldt
+license: https://github.com/NVIDIA-AI-IOT/nanosam/tree/main
+meta:
+  FPS:
+    mean: 2.0
+    std: 0.1
+  backbone: ResNet18
+  downloads:
+  - name: nanosam_resnet18_image_encoder_1024x1024.xml
+    url: https://github.com/luxonis/depthai-model-zoo/raw/main/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml
+  - name: nanosam_resnet18_image_encoder_1024x1024.bin
+    url: https://robothub.fra1.cdn.digitaloceanspaces.com/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.bin
+  experiment: https://github.com/luxonis/depthai-experiments/tree/master/gen2-nanosam
+  featured: false
+  inputs:
+  - name: images
+    shape: 3, 1024, 1024
+    type: image
+  license:
+    name: Apache-2.0
+    url: https://opensource.org/licenses/Apache-2.0
+  source:
+  - name: NanoSAM
+    url: https://github.com/NVIDIA-AI-IOT/nanosam
+  uses_depth: false
+  verbose_name: NanoSAM embedder
+task_type: classification
diff --git a/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml b/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml
new file mode 100644
index 0000000..73fab37
--- /dev/null
+++ b/models/nanosam_resnet18_image_encoder_1024x1024/nanosam_resnet18_image_encoder_1024x1024.xml
@@ -0,0 +1,4260 @@
+<?xml version="1.0" ?>
+<net name="torch_jit" version="11">
+	<layers>
+		<layer id="0" name="image" type="Parameter" version="opset1">
+			<data shape="1,3,1024,1024" element_type="f32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="image"/>
+				<attribute name="old_api_map_element_type" version="0" value="f16"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="image">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1024</dim>
+					<dim>1024</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="Gather_3167_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 3, 1, 1" offset="0" 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="2" name="Gather_3167" 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>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="3" name="Subtract_1339" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Subtract_1339"/>
+				<attribute name="preprocessing" version="0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1024</dim>
+					<dim>1024</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>1024</dim>
+					<dim>1024</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Gather_3170_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="64, 3, 7, 7" offset="6" size="18816"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>7</dim>
+					<dim>7</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="Gather_3170" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>7</dim>
+					<dim>7</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>7</dim>
+					<dim>7</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="Convolution_54" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="3, 3" pads_end="3, 3" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Constant_1340, Convolution_54, Divide_1341, onnx::Conv_248"/>
+				<attribute name="preprocessing" version="0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1024</dim>
+					<dim>1024</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>7</dim>
+					<dim>7</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Reshape_74_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 64, 1, 1" offset="18822" size="128"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="Reshape_74" 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>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="/backbone/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/conv1/Conv_output_0, Concat_73, Reshape_74"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="/backbone/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="/backbone/maxpool/MaxPool_output_0" type="MaxPool" version="opset8">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" kernel="3, 3" rounding_type="floor" auto_pad="explicit" index_element_type="i64" axis="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/maxpool/MaxPool_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>512</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/maxpool/MaxPool_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="onnx::Conv_251_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="64, 64, 3, 3" offset="18950" size="73728"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="onnx::Conv_251" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_251"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_251">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="Convolution_104" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_104"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="Reshape_124_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 64, 1, 1" offset="92678" size="128"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="Reshape_124" 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>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="/backbone/layer1/layer1.0/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.0/conv1/Conv_output_0, Concat_123, Reshape_124"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.0/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="/backbone/layer1/layer1.0/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.0/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer1/layer1.0/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="onnx::Conv_254_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="64, 64, 3, 3" offset="92806" size="73728"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="onnx::Conv_254" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_254"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_254">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="Convolution_153" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_153"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="Reshape_173_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 64, 1, 1" offset="166534" size="128"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="Reshape_173" 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>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="/backbone/layer1/layer1.0/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.0/conv2/Conv_output_0, Concat_172, Reshape_173"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.0/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="/backbone/layer1/layer1.0/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.0/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.0/Add_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="/backbone/layer1/layer1.0/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.0/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer1/layer1.0/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="onnx::Conv_257_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="64, 64, 3, 3" offset="166662" size="73728"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="onnx::Conv_257" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_257"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_257">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="Convolution_203" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_203"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="Reshape_223_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 64, 1, 1" offset="240390" size="128"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="31" name="Reshape_223" 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>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="/backbone/layer1/layer1.1/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.1/conv1/Conv_output_0, Concat_222, Reshape_223"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.1/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="33" name="/backbone/layer1/layer1.1/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.1/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer1/layer1.1/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="34" name="onnx::Conv_260_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="64, 64, 3, 3" offset="240518" size="73728"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="35" name="onnx::Conv_260" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_260"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_260">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="36" name="Convolution_252" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_252"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>64</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="37" name="Reshape_272_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 64, 1, 1" offset="314246" size="128"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="38" name="Reshape_272" 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>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="39" name="/backbone/layer1/layer1.1/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.1/conv2/Conv_output_0, Concat_271, Reshape_272"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.1/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="40" name="/backbone/layer1/layer1.1/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.1/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer1/layer1.1/Add_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="41" name="/backbone/layer1/layer1.1/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer1/layer1.1/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer1/layer1.1/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="42" name="onnx::Conv_263_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="128, 64, 3, 3" offset="314374" size="147456"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="43" name="onnx::Conv_263" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_263"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_263">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="44" name="Convolution_302" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_302"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="45" name="Reshape_322_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 128, 1, 1" offset="461830" size="256"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="46" name="Reshape_322" 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>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="47" name="/backbone/layer2/layer2.0/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/conv1/Conv_output_0, Concat_321, Reshape_322"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.0/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="48" name="/backbone/layer2/layer2.0/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer2/layer2.0/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="49" name="onnx::Conv_266_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="128, 128, 3, 3" offset="462086" size="294912"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="50" name="onnx::Conv_266" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_266"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_266">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="51" name="Convolution_351" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_351"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="52" name="Reshape_371_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 128, 1, 1" offset="756998" size="256"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="53" name="Reshape_371" 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>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="54" name="/backbone/layer2/layer2.0/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/conv2/Conv_output_0, Concat_370, Reshape_371"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.0/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="55" name="onnx::Conv_269_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="128, 64, 1, 1" offset="757254" size="16384"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="56" name="onnx::Conv_269" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_269"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_269">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="57" name="Convolution_399" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_399"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>64</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>64</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="58" name="Reshape_419_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 128, 1, 1" offset="773638" size="256"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="59" name="Reshape_419" 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>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="60" name="/backbone/layer2/layer2.0/downsample/downsample.0/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/downsample/downsample.0/Conv_output_0, Concat_418, Reshape_419"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.0/downsample/downsample.0/Conv_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="61" name="/backbone/layer2/layer2.0/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.0/Add_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="62" name="/backbone/layer2/layer2.0/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.0/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer2/layer2.0/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="63" name="onnx::Conv_272_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="128, 128, 3, 3" offset="773894" size="294912"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="64" name="onnx::Conv_272" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_272"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_272">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="65" name="Convolution_449" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_449"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="66" name="Reshape_469_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 128, 1, 1" offset="1068806" size="256"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="67" name="Reshape_469" 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>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="68" name="/backbone/layer2/layer2.1/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.1/conv1/Conv_output_0, Concat_468, Reshape_469"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.1/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="69" name="/backbone/layer2/layer2.1/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.1/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer2/layer2.1/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="70" name="onnx::Conv_275_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="128, 128, 3, 3" offset="1069062" size="294912"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="71" name="onnx::Conv_275" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_275"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_275">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="72" name="Convolution_498" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_498"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="73" name="Reshape_518_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 128, 1, 1" offset="1363974" size="256"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="74" name="Reshape_518" 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>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="75" name="/backbone/layer2/layer2.1/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.1/conv2/Conv_output_0, Concat_517, Reshape_518"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.1/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="76" name="/backbone/layer2/layer2.1/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.1/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer2/layer2.1/Add_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="77" name="/backbone/layer2/layer2.1/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer2/layer2.1/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer2/layer2.1/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="78" name="onnx::Conv_278_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 128, 3, 3" offset="1364230" size="589824"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="79" name="onnx::Conv_278" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_278"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_278">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="80" name="Convolution_548" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_548"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="81" name="Reshape_568_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="1954054" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="82" name="Reshape_568" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="83" name="/backbone/layer3/layer3.0/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/conv1/Conv_output_0, Concat_567, Reshape_568"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.0/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="84" name="/backbone/layer3/layer3.0/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer3/layer3.0/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="85" name="onnx::Conv_281_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="1954566" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="86" name="onnx::Conv_281" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_281"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_281">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="87" name="Convolution_597" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_597"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="88" name="Reshape_617_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="3134214" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="89" name="Reshape_617" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="90" name="/backbone/layer3/layer3.0/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/conv2/Conv_output_0, Concat_616, Reshape_617"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.0/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="91" name="onnx::Conv_284_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 128, 1, 1" offset="3134726" size="65536"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="92" name="onnx::Conv_284" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_284"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_284">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="93" name="Convolution_645" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_645"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>128</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="94" name="Reshape_665_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="3200262" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="95" name="Reshape_665" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="96" name="/backbone/layer3/layer3.0/downsample/downsample.0/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/downsample/downsample.0/Conv_output_0, Concat_664, Reshape_665"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.0/downsample/downsample.0/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="97" name="/backbone/layer3/layer3.0/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.0/Add_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="98" name="/backbone/layer3/layer3.0/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.0/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer3/layer3.0/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="99" name="onnx::Conv_287_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="3200774" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="100" name="onnx::Conv_287" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_287"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_287">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="101" name="Convolution_695" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_695"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="102" name="Reshape_715_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="4380422" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="103" name="Reshape_715" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="104" name="/backbone/layer3/layer3.1/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.1/conv1/Conv_output_0, Concat_714, Reshape_715"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.1/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="105" name="/backbone/layer3/layer3.1/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.1/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer3/layer3.1/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="106" name="onnx::Conv_290_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="4380934" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="107" name="onnx::Conv_290" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_290"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_290">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="108" name="Convolution_744" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_744"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="109" name="Reshape_764_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="5560582" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="110" name="Reshape_764" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="111" name="/backbone/layer3/layer3.1/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.1/conv2/Conv_output_0, Concat_763, Reshape_764"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.1/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="112" name="/backbone/layer3/layer3.1/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.1/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer3/layer3.1/Add_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="113" name="/backbone/layer3/layer3.1/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer3/layer3.1/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer3/layer3.1/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="114" name="onnx::Conv_293_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 256, 3, 3" offset="5561094" size="2359296"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="115" name="onnx::Conv_293" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_293"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_293">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="116" name="Convolution_794" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_794"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="117" name="Reshape_814_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 512, 1, 1" offset="7920390" size="1024"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="118" name="Reshape_814" 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>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="119" name="/backbone/layer4/layer4.0/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/conv1/Conv_output_0, Concat_813, Reshape_814"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.0/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="120" name="/backbone/layer4/layer4.0/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer4/layer4.0/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="121" name="onnx::Conv_296_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 512, 3, 3" offset="7921414" size="4718592"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="122" name="onnx::Conv_296" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_296"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_296">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="123" name="Convolution_843" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_843"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="124" name="Reshape_863_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 512, 1, 1" offset="12640006" size="1024"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="125" name="Reshape_863" 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>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="126" name="/backbone/layer4/layer4.0/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/conv2/Conv_output_0, Concat_862, Reshape_863"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.0/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="127" name="onnx::Conv_299_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 256, 1, 1" offset="12641030" size="262144"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="128" name="onnx::Conv_299" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_299"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_299">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="129" name="Convolution_891" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_891"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="130" name="Reshape_911_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 512, 1, 1" offset="12903174" size="1024"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="131" name="Reshape_911" 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>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="132" name="/backbone/layer4/layer4.0/downsample/downsample.0/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/downsample/downsample.0/Conv_output_0, Concat_910, Reshape_911"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.0/downsample/downsample.0/Conv_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="133" name="/backbone/layer4/layer4.0/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.0/Add_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="134" name="/backbone/layer4/layer4.0/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.0/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer4/layer4.0/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="135" name="onnx::Conv_302_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 512, 3, 3" offset="12904198" size="4718592"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="136" name="onnx::Conv_302" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_302"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_302">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="137" name="Convolution_941" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_941"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="138" name="Reshape_961_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 512, 1, 1" offset="17622790" size="1024"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="139" name="Reshape_961" 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>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="140" name="/backbone/layer4/layer4.1/conv1/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.1/conv1/Conv_output_0, Concat_960, Reshape_961"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.1/conv1/Conv_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="141" name="/backbone/layer4/layer4.1/act1/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.1/act1/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer4/layer4.1/act1/Relu_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="142" name="onnx::Conv_305_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 512, 3, 3" offset="17623814" size="4718592"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="143" name="onnx::Conv_305" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="onnx::Conv_305"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="onnx::Conv_305">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="144" name="Convolution_990" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_990"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>512</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="145" name="Reshape_1010_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 512, 1, 1" offset="22342406" size="1024"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="146" name="Reshape_1010" 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>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="147" name="/backbone/layer4/layer4.1/conv2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.1/conv2/Conv_output_0, Concat_1009, Reshape_1010"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.1/conv2/Conv_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="148" name="/backbone/layer4/layer4.1/Add_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.1/Add_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/backbone/layer4/layer4.1/Add_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="149" name="/backbone/layer4/layer4.1/act2/Relu_output_0" type="ReLU" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/backbone/layer4/layer4.1/act2/Relu_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/backbone/layer4/layer4.1/act2/Relu_output_0">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="150" name="up_1.0.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 512, 3, 3" offset="22343430" size="2359296"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="151" name="up_1.0.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="up_1.0.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="up_1.0.weight">
+					<dim>256</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="152" name="Convolution_1040" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_1040"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>512</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>512</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="153" name="Reshape_1060_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="24702726" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="154" name="Reshape_1060" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="155" name="/up_1/up_1.0/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.0/Conv_output_0, Concat_1059, Reshape_1060"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/up_1/up_1.0/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="156" name="/up_1/up_1.1/Mul_1_output_0" type="Gelu" version="opset7">
+			<data approximation_mode="ERF"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.1/Add_output_0, /up_1/up_1.1/Div_output_0, /up_1/up_1.1/Erf_output_0, /up_1/up_1.1/Mul_1_output_0, /up_1/up_1.1/Mul_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/up_1/up_1.1/Mul_1_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="157" name="up_1.2.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="24703238" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="158" name="up_1.2.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="up_1.2.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="up_1.2.weight">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="159" name="Convolution_1096" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_1096"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="160" name="Reshape_1116_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="25882886" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="161" name="Reshape_1116" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="162" name="/up_1/up_1.2/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.2/Conv_output_0, Concat_1115, Reshape_1116"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/up_1/up_1.2/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="163" name="/up_1/up_1.3/Mul_1_output_0" type="Gelu" version="opset7">
+			<data approximation_mode="ERF"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.3/Add_output_0, /up_1/up_1.3/Div_output_0, /up_1/up_1.3/Erf_output_0, /up_1/up_1.3/Mul_1_output_0, /up_1/up_1.3/Mul_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/up_1/up_1.3/Mul_1_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="164" name="up_1.4.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="25883398" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="165" name="up_1.4.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="up_1.4.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="up_1.4.weight">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="166" name="Convolution_1152" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_1152"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="167" name="Reshape_1172_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="27063046" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="168" name="Reshape_1172" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="169" name="/up_1/up_1.4/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.4/Conv_output_0, Concat_1171, Reshape_1172"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/up_1/up_1.4/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="170" name="/up_1/up_1.5/Mul_1_output_0" type="Gelu" version="opset7">
+			<data approximation_mode="ERF"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.5/Add_output_0, /up_1/up_1.5/Div_output_0, /up_1/up_1.5/Erf_output_0, /up_1/up_1.5/Mul_1_output_0, /up_1/up_1.5/Mul_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/up_1/up_1.5/Mul_1_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="171" name="up_1.6.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="27063558" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="172" name="up_1.6.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="up_1.6.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="up_1.6.weight">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="173" name="ConvolutionBackpropData_1208" type="ConvolutionBackpropData" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" output_padding="1, 1"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="ConvolutionBackpropData_1208"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>32</dim>
+					<dim>32</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="174" name="Reshape_1210_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="28243206" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="175" name="Reshape_1210" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="176" name="/up_1/up_1.6/ConvTranspose_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.6/ConvTranspose_output_0, Reshape_1210"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/up_1/up_1.6/ConvTranspose_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="177" name="/up_1/up_1.7/Mul_1_output_0" type="Gelu" version="opset7">
+			<data approximation_mode="ERF"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/up_1/up_1.7/Add_output_0, /up_1/up_1.7/Div_output_0, /up_1/up_1.7/Erf_output_0, /up_1/up_1.7/Mul_1_output_0, /up_1/up_1.7/Mul_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/up_1/up_1.7/Mul_1_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="178" name="proj.0.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 3, 3" offset="28243718" size="1179648"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="179" name="proj.0.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="proj.0.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="proj.0.weight">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="180" name="Convolution_1225" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_1225"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="181" name="Reshape_1245_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 1, 1" offset="29423366" size="512"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="182" name="Reshape_1245" 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>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="183" name="/proj/proj.0/Conv_output_0" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/proj/proj.0/Conv_output_0, Concat_1244, Reshape_1245"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/proj/proj.0/Conv_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="184" name="/proj/proj.1/Mul_1_output_0" type="Gelu" version="opset7">
+			<data approximation_mode="ERF"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/proj/proj.1/Add_output_0, /proj/proj.1/Div_output_0, /proj/proj.1/Erf_output_0, /proj/proj.1/Mul_1_output_0, /proj/proj.1/Mul_output_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/proj/proj.1/Mul_1_output_0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="185" name="proj.2.weight_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="256, 256, 1, 1" offset="29423878" size="131072"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="186" name="proj.2.weight" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="proj.2.weight"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="proj.2.weight">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="187" name="Convolution_1281" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="Convolution_1281"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="188" name="Constant_3117_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 256, 64, 64" offset="29554950" size="2097152"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="189" name="Constant_3117" 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>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="190" name="image_embeddings" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="/proj/proj.2/Conv_output_0, Concat_1300, Reshape_1301, image_embeddings"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="image_embeddings">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="191" name="image_embeddings/sink_port_0" type="Result" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="image_embeddings/sink_port_0"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>64</dim>
+					<dim>64</dim>
+				</port>
+			</input>
+		</layer>
+	</layers>
+	<edges>
+		<edge from-layer="0" from-port="0" to-layer="3" to-port="0"/>
+		<edge from-layer="1" from-port="0" to-layer="2" to-port="0"/>
+		<edge from-layer="2" from-port="1" to-layer="3" to-port="1"/>
+		<edge from-layer="3" from-port="2" to-layer="6" to-port="0"/>
+		<edge from-layer="4" from-port="0" to-layer="5" to-port="0"/>
+		<edge from-layer="5" from-port="1" to-layer="6" to-port="1"/>
+		<edge from-layer="6" from-port="2" to-layer="9" to-port="0"/>
+		<edge from-layer="7" from-port="0" to-layer="8" to-port="0"/>
+		<edge from-layer="8" from-port="1" to-layer="9" to-port="1"/>
+		<edge from-layer="9" from-port="2" to-layer="10" to-port="0"/>
+		<edge from-layer="10" from-port="1" to-layer="11" to-port="0"/>
+		<edge from-layer="11" from-port="1" to-layer="14" to-port="0"/>
+		<edge from-layer="11" from-port="1" to-layer="25" to-port="1"/>
+		<edge from-layer="12" from-port="0" to-layer="13" to-port="0"/>
+		<edge from-layer="13" from-port="1" to-layer="14" to-port="1"/>
+		<edge from-layer="14" from-port="2" to-layer="17" to-port="0"/>
+		<edge from-layer="15" from-port="0" to-layer="16" to-port="0"/>
+		<edge from-layer="16" from-port="1" to-layer="17" to-port="1"/>
+		<edge from-layer="17" from-port="2" to-layer="18" to-port="0"/>
+		<edge from-layer="18" from-port="1" to-layer="21" to-port="0"/>
+		<edge from-layer="19" from-port="0" to-layer="20" to-port="0"/>
+		<edge from-layer="20" from-port="1" to-layer="21" to-port="1"/>
+		<edge from-layer="21" from-port="2" to-layer="24" to-port="0"/>
+		<edge from-layer="22" from-port="0" to-layer="23" to-port="0"/>
+		<edge from-layer="23" from-port="1" to-layer="24" to-port="1"/>
+		<edge from-layer="24" from-port="2" to-layer="25" to-port="0"/>
+		<edge from-layer="25" from-port="2" to-layer="26" to-port="0"/>
+		<edge from-layer="26" from-port="1" to-layer="29" to-port="0"/>
+		<edge from-layer="26" from-port="1" to-layer="40" to-port="1"/>
+		<edge from-layer="27" from-port="0" to-layer="28" to-port="0"/>
+		<edge from-layer="28" from-port="1" to-layer="29" to-port="1"/>
+		<edge from-layer="29" from-port="2" to-layer="32" to-port="0"/>
+		<edge from-layer="30" from-port="0" to-layer="31" to-port="0"/>
+		<edge from-layer="31" from-port="1" to-layer="32" to-port="1"/>
+		<edge from-layer="32" from-port="2" to-layer="33" to-port="0"/>
+		<edge from-layer="33" from-port="1" to-layer="36" to-port="0"/>
+		<edge from-layer="34" from-port="0" to-layer="35" to-port="0"/>
+		<edge from-layer="35" from-port="1" to-layer="36" to-port="1"/>
+		<edge from-layer="36" from-port="2" to-layer="39" to-port="0"/>
+		<edge from-layer="37" from-port="0" to-layer="38" to-port="0"/>
+		<edge from-layer="38" from-port="1" to-layer="39" to-port="1"/>
+		<edge from-layer="39" from-port="2" to-layer="40" to-port="0"/>
+		<edge from-layer="40" from-port="2" to-layer="41" to-port="0"/>
+		<edge from-layer="41" from-port="1" to-layer="44" to-port="0"/>
+		<edge from-layer="41" from-port="1" to-layer="57" to-port="0"/>
+		<edge from-layer="42" from-port="0" to-layer="43" to-port="0"/>
+		<edge from-layer="43" from-port="1" to-layer="44" to-port="1"/>
+		<edge from-layer="44" from-port="2" to-layer="47" to-port="0"/>
+		<edge from-layer="45" from-port="0" to-layer="46" to-port="0"/>
+		<edge from-layer="46" from-port="1" to-layer="47" to-port="1"/>
+		<edge from-layer="47" from-port="2" to-layer="48" to-port="0"/>
+		<edge from-layer="48" from-port="1" to-layer="51" to-port="0"/>
+		<edge from-layer="49" from-port="0" to-layer="50" to-port="0"/>
+		<edge from-layer="50" from-port="1" to-layer="51" to-port="1"/>
+		<edge from-layer="51" from-port="2" to-layer="54" to-port="0"/>
+		<edge from-layer="52" from-port="0" to-layer="53" to-port="0"/>
+		<edge from-layer="53" from-port="1" to-layer="54" to-port="1"/>
+		<edge from-layer="54" from-port="2" to-layer="61" to-port="0"/>
+		<edge from-layer="55" from-port="0" to-layer="56" to-port="0"/>
+		<edge from-layer="56" from-port="1" to-layer="57" to-port="1"/>
+		<edge from-layer="57" from-port="2" to-layer="60" to-port="0"/>
+		<edge from-layer="58" from-port="0" to-layer="59" to-port="0"/>
+		<edge from-layer="59" from-port="1" to-layer="60" to-port="1"/>
+		<edge from-layer="60" from-port="2" to-layer="61" to-port="1"/>
+		<edge from-layer="61" from-port="2" to-layer="62" to-port="0"/>
+		<edge from-layer="62" from-port="1" to-layer="76" to-port="1"/>
+		<edge from-layer="62" from-port="1" to-layer="65" to-port="0"/>
+		<edge from-layer="63" from-port="0" to-layer="64" to-port="0"/>
+		<edge from-layer="64" from-port="1" to-layer="65" to-port="1"/>
+		<edge from-layer="65" from-port="2" to-layer="68" to-port="0"/>
+		<edge from-layer="66" from-port="0" to-layer="67" to-port="0"/>
+		<edge from-layer="67" from-port="1" to-layer="68" to-port="1"/>
+		<edge from-layer="68" from-port="2" to-layer="69" to-port="0"/>
+		<edge from-layer="69" from-port="1" to-layer="72" to-port="0"/>
+		<edge from-layer="70" from-port="0" to-layer="71" to-port="0"/>
+		<edge from-layer="71" from-port="1" to-layer="72" to-port="1"/>
+		<edge from-layer="72" from-port="2" to-layer="75" to-port="0"/>
+		<edge from-layer="73" from-port="0" to-layer="74" to-port="0"/>
+		<edge from-layer="74" from-port="1" to-layer="75" to-port="1"/>
+		<edge from-layer="75" from-port="2" to-layer="76" to-port="0"/>
+		<edge from-layer="76" from-port="2" to-layer="77" to-port="0"/>
+		<edge from-layer="77" from-port="1" to-layer="80" to-port="0"/>
+		<edge from-layer="77" from-port="1" to-layer="93" to-port="0"/>
+		<edge from-layer="78" from-port="0" to-layer="79" to-port="0"/>
+		<edge from-layer="79" from-port="1" to-layer="80" to-port="1"/>
+		<edge from-layer="80" from-port="2" to-layer="83" to-port="0"/>
+		<edge from-layer="81" from-port="0" to-layer="82" to-port="0"/>
+		<edge from-layer="82" from-port="1" to-layer="83" to-port="1"/>
+		<edge from-layer="83" from-port="2" to-layer="84" to-port="0"/>
+		<edge from-layer="84" from-port="1" to-layer="87" to-port="0"/>
+		<edge from-layer="85" from-port="0" to-layer="86" to-port="0"/>
+		<edge from-layer="86" from-port="1" to-layer="87" to-port="1"/>
+		<edge from-layer="87" from-port="2" to-layer="90" to-port="0"/>
+		<edge from-layer="88" from-port="0" to-layer="89" to-port="0"/>
+		<edge from-layer="89" from-port="1" to-layer="90" to-port="1"/>
+		<edge from-layer="90" from-port="2" to-layer="97" to-port="0"/>
+		<edge from-layer="91" from-port="0" to-layer="92" to-port="0"/>
+		<edge from-layer="92" from-port="1" to-layer="93" to-port="1"/>
+		<edge from-layer="93" from-port="2" to-layer="96" to-port="0"/>
+		<edge from-layer="94" from-port="0" to-layer="95" to-port="0"/>
+		<edge from-layer="95" from-port="1" to-layer="96" to-port="1"/>
+		<edge from-layer="96" from-port="2" to-layer="97" to-port="1"/>
+		<edge from-layer="97" from-port="2" to-layer="98" to-port="0"/>
+		<edge from-layer="98" from-port="1" to-layer="101" to-port="0"/>
+		<edge from-layer="98" from-port="1" to-layer="112" to-port="1"/>
+		<edge from-layer="99" from-port="0" to-layer="100" to-port="0"/>
+		<edge from-layer="100" from-port="1" to-layer="101" to-port="1"/>
+		<edge from-layer="101" from-port="2" to-layer="104" to-port="0"/>
+		<edge from-layer="102" from-port="0" to-layer="103" to-port="0"/>
+		<edge from-layer="103" from-port="1" to-layer="104" to-port="1"/>
+		<edge from-layer="104" from-port="2" to-layer="105" to-port="0"/>
+		<edge from-layer="105" from-port="1" to-layer="108" to-port="0"/>
+		<edge from-layer="106" from-port="0" to-layer="107" to-port="0"/>
+		<edge from-layer="107" from-port="1" to-layer="108" to-port="1"/>
+		<edge from-layer="108" from-port="2" to-layer="111" to-port="0"/>
+		<edge from-layer="109" from-port="0" to-layer="110" to-port="0"/>
+		<edge from-layer="110" from-port="1" to-layer="111" to-port="1"/>
+		<edge from-layer="111" from-port="2" to-layer="112" to-port="0"/>
+		<edge from-layer="112" from-port="2" to-layer="113" to-port="0"/>
+		<edge from-layer="113" from-port="1" to-layer="116" to-port="0"/>
+		<edge from-layer="113" from-port="1" to-layer="129" to-port="0"/>
+		<edge from-layer="114" from-port="0" to-layer="115" to-port="0"/>
+		<edge from-layer="115" from-port="1" to-layer="116" to-port="1"/>
+		<edge from-layer="116" from-port="2" to-layer="119" to-port="0"/>
+		<edge from-layer="117" from-port="0" to-layer="118" to-port="0"/>
+		<edge from-layer="118" from-port="1" to-layer="119" to-port="1"/>
+		<edge from-layer="119" from-port="2" to-layer="120" to-port="0"/>
+		<edge from-layer="120" from-port="1" to-layer="123" to-port="0"/>
+		<edge from-layer="121" from-port="0" to-layer="122" to-port="0"/>
+		<edge from-layer="122" from-port="1" to-layer="123" to-port="1"/>
+		<edge from-layer="123" from-port="2" to-layer="126" to-port="0"/>
+		<edge from-layer="124" from-port="0" to-layer="125" to-port="0"/>
+		<edge from-layer="125" from-port="1" to-layer="126" to-port="1"/>
+		<edge from-layer="126" from-port="2" to-layer="133" to-port="0"/>
+		<edge from-layer="127" from-port="0" to-layer="128" to-port="0"/>
+		<edge from-layer="128" from-port="1" to-layer="129" to-port="1"/>
+		<edge from-layer="129" from-port="2" to-layer="132" to-port="0"/>
+		<edge from-layer="130" from-port="0" to-layer="131" to-port="0"/>
+		<edge from-layer="131" from-port="1" to-layer="132" to-port="1"/>
+		<edge from-layer="132" from-port="2" to-layer="133" to-port="1"/>
+		<edge from-layer="133" from-port="2" to-layer="134" to-port="0"/>
+		<edge from-layer="134" from-port="1" to-layer="137" to-port="0"/>
+		<edge from-layer="134" from-port="1" to-layer="148" to-port="1"/>
+		<edge from-layer="135" from-port="0" to-layer="136" to-port="0"/>
+		<edge from-layer="136" from-port="1" to-layer="137" to-port="1"/>
+		<edge from-layer="137" from-port="2" to-layer="140" to-port="0"/>
+		<edge from-layer="138" from-port="0" to-layer="139" to-port="0"/>
+		<edge from-layer="139" from-port="1" to-layer="140" to-port="1"/>
+		<edge from-layer="140" from-port="2" to-layer="141" to-port="0"/>
+		<edge from-layer="141" from-port="1" to-layer="144" to-port="0"/>
+		<edge from-layer="142" from-port="0" to-layer="143" to-port="0"/>
+		<edge from-layer="143" from-port="1" to-layer="144" to-port="1"/>
+		<edge from-layer="144" from-port="2" to-layer="147" to-port="0"/>
+		<edge from-layer="145" from-port="0" to-layer="146" to-port="0"/>
+		<edge from-layer="146" from-port="1" to-layer="147" to-port="1"/>
+		<edge from-layer="147" from-port="2" to-layer="148" to-port="0"/>
+		<edge from-layer="148" from-port="2" to-layer="149" to-port="0"/>
+		<edge from-layer="149" from-port="1" to-layer="152" to-port="0"/>
+		<edge from-layer="150" from-port="0" to-layer="151" to-port="0"/>
+		<edge from-layer="151" from-port="1" to-layer="152" to-port="1"/>
+		<edge from-layer="152" from-port="2" to-layer="155" to-port="0"/>
+		<edge from-layer="153" from-port="0" to-layer="154" to-port="0"/>
+		<edge from-layer="154" from-port="1" to-layer="155" to-port="1"/>
+		<edge from-layer="155" from-port="2" to-layer="156" to-port="0"/>
+		<edge from-layer="156" from-port="1" to-layer="159" to-port="0"/>
+		<edge from-layer="157" from-port="0" to-layer="158" to-port="0"/>
+		<edge from-layer="158" from-port="1" to-layer="159" to-port="1"/>
+		<edge from-layer="159" from-port="2" to-layer="162" to-port="0"/>
+		<edge from-layer="160" from-port="0" to-layer="161" to-port="0"/>
+		<edge from-layer="161" from-port="1" to-layer="162" to-port="1"/>
+		<edge from-layer="162" from-port="2" to-layer="163" to-port="0"/>
+		<edge from-layer="163" from-port="1" to-layer="166" to-port="0"/>
+		<edge from-layer="164" from-port="0" to-layer="165" to-port="0"/>
+		<edge from-layer="165" from-port="1" to-layer="166" to-port="1"/>
+		<edge from-layer="166" from-port="2" to-layer="169" to-port="0"/>
+		<edge from-layer="167" from-port="0" to-layer="168" to-port="0"/>
+		<edge from-layer="168" from-port="1" to-layer="169" to-port="1"/>
+		<edge from-layer="169" from-port="2" to-layer="170" to-port="0"/>
+		<edge from-layer="170" from-port="1" to-layer="173" to-port="0"/>
+		<edge from-layer="171" from-port="0" to-layer="172" to-port="0"/>
+		<edge from-layer="172" from-port="1" to-layer="173" to-port="1"/>
+		<edge from-layer="173" from-port="2" to-layer="176" to-port="0"/>
+		<edge from-layer="174" from-port="0" to-layer="175" to-port="0"/>
+		<edge from-layer="175" from-port="1" to-layer="176" to-port="1"/>
+		<edge from-layer="176" from-port="2" to-layer="177" to-port="0"/>
+		<edge from-layer="177" from-port="1" to-layer="180" to-port="0"/>
+		<edge from-layer="178" from-port="0" to-layer="179" to-port="0"/>
+		<edge from-layer="179" from-port="1" to-layer="180" to-port="1"/>
+		<edge from-layer="180" from-port="2" to-layer="183" to-port="0"/>
+		<edge from-layer="181" from-port="0" to-layer="182" to-port="0"/>
+		<edge from-layer="182" from-port="1" to-layer="183" to-port="1"/>
+		<edge from-layer="183" from-port="2" to-layer="184" to-port="0"/>
+		<edge from-layer="184" from-port="1" to-layer="187" to-port="0"/>
+		<edge from-layer="185" from-port="0" to-layer="186" to-port="0"/>
+		<edge from-layer="186" from-port="1" to-layer="187" to-port="1"/>
+		<edge from-layer="187" from-port="2" to-layer="190" to-port="0"/>
+		<edge from-layer="188" from-port="0" to-layer="189" to-port="0"/>
+		<edge from-layer="189" from-port="1" to-layer="190" to-port="1"/>
+		<edge from-layer="190" from-port="2" to-layer="191" to-port="0"/>
+	</edges>
+	<meta_data>
+		<MO_version value="2022.1.0-7019-cdb9bec7210-releases/2022/1"/>
+		<Runtime_version value="2022.1.0-7080-6582ec65d78-releases/2022/1"/>
+		<legacy_path value="False"/>
+		<cli_parameters>
+			<caffe_parser_path value="DIR"/>
+			<compress_fp16 value="True"/>
+			<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="onnx"/>
+			<freeze_placeholder_with_value value="{}"/>
+			<input_model value="DIR/resnet18_image_encoder.onnx"/>
+			<input_model_is_text value="False"/>
+			<k value="DIR/CustomLayersMapping.xml"/>
+			<layout value="()"/>
+			<layout_values value="{}"/>
+			<legacy_mxnet_model value="False"/>
+			<log_level value="ERROR"/>
+			<mean_scale_values value="[(array([123.675, 116.28 , 103.53 ]), array([58.395, 57.12 , 57.375]))]"/>
+			<mean_values value="[123.675,116.28,103.53]"/>
+			<model_name value="resnet18_image_encoder"/>
+			<output_dir value="DIR"/>
+			<placeholder_data_types value="{}"/>
+			<progress value="False"/>
+			<remove_memory value="False"/>
+			<remove_output_softmax value="False"/>
+			<reverse_input_channels value="True"/>
+			<save_params_from_nd value="False"/>
+			<scale_values value="[58.395,57.12,57.375]"/>
+			<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, input_checkpoint, input_meta_graph, input_proto, input_shape, input_symbol, mean_file, mean_file_offsets, nd_prefix_name, output, placeholder_shapes, 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>

From 61c4ea6e4c7fd545857ab946f5326f64006cc7ac Mon Sep 17 00:00:00 2001
From: tersekmatija <matija@luxonis.com>
Date: Fri, 6 Oct 2023 15:49:53 +0200
Subject: [PATCH 2/2] Fix task

---
 models/nanosam_resnet18_image_encoder_1024x1024/model.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/models/nanosam_resnet18_image_encoder_1024x1024/model.yml b/models/nanosam_resnet18_image_encoder_1024x1024/model.yml
index 95f0f12..8cc9109 100644
--- a/models/nanosam_resnet18_image_encoder_1024x1024/model.yml
+++ b/models/nanosam_resnet18_image_encoder_1024x1024/model.yml
@@ -37,4 +37,4 @@ meta:
     url: https://github.com/NVIDIA-AI-IOT/nanosam
   uses_depth: false
   verbose_name: NanoSAM embedder
-task_type: classification
+task_type: feature_extraction