onnx-subgraph tool step by step submitting initial PR

tools/onnx-subgraph/CMakeLists.txt

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+# cmake version dependency
+cmake_minimum_required(VERSION 3.10)
+
+set(ONNX_SUGRAPH_FILES                                                          
+    extract_onnx.py
+    test_model_download.sh
+    subgraphs_ios.txt
+ )                                                                            
+
+ foreach(ONNX_SUGRAPH IN ITEMS ${ONNX_SUGRAPH_FILES})                                                                                                        
+   set(ONNX_SUGRAPH_FILE ${ONNX_SUGRAPH})                                           
+   set(ONNX_SUGRAPH_SRC "${CMAKE_CURRENT_SOURCE_DIR}/${ONNX_SUGRAPH_FILE}")         
+   set(ONNX_SUGRAPH_BIN "${CMAKE_CURRENT_BINARY_DIR}/scripts/${ONNX_SUGRAPH_FILE}")         
+   set(ONNX_SUGRAPH_TARGET "${ONNX_SUGRAPH}_target")                                
+
+   add_custom_command(OUTPUT ${ONNX_SUGRAPH_BIN}                                 
+     COMMAND ${CMAKE_COMMAND} -E copy "${ONNX_SUGRAPH_SRC}" "${ONNX_SUGRAPH_BIN}"   
+     DEPENDS ${ONNX_SUGRAPH_SRC}                                                 
+     COMMENT "Generate ${ONNX_SUGRAPH_BIN}"                                      
+   )                                                                          
+
+   add_custom_target(${ONNX_SUGRAPH_TARGET} ALL DEPENDS ${ONNX_SUGRAPH_BIN})        
+
+   install(FILES ${ONNX_SUGRAPH_BIN}                                             
+           PERMISSIONS OWNER_WRITE OWNER_READ OWNER_EXECUTE                   
+                       GROUP_READ GROUP_EXECUTE                               
+                       WORLD_READ WORLD_EXECUTE                               
+           DESTINATION bin)                                                   
+
+ endforeach(ONNX_SUGRAPH)     

tools/onnx-subgraph/Readme.md

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+# onnx_autosubgraph
+onnx-subgraph tool provides  model auto partitionioning of onnx model to several sub models by 
+operator, performance and model size limitations,with the order and input / output names of 
+sub models
+
+# How to build the onnx-subgraph
+## OS environment dependence
+     1. ubuntu >=20.04
+     2. GCC >= 9.4.0
+     3. cmake >= 3.10
+     4. python >= 3.8
+     5. apt-get install libprotobuf-dev protobuf-compiler libjsoncpp-dev
+
+## Python packages dependence
+    onnx                         1.16.0
+    onnxruntime                  1.18.1
+    onnxsim                      0.4.36
+    torch                        2.3.1
+    scikit-image
+    scikit-learn
+    pandas
+    tqdm
+
+## building the onnx-subgraph
+    1. cd onnx-subgraph
+    2. mkdir build & cd build
+    3. cmake .. & make
+    4. we can get following output at ./build
+          └── scripts
+              ├── extract_onnx.py
+              └── test_model_download.sh
+              └── subgraphs_ios.txt
+
+# How to use the onnx-subgraph
+## Pre-steps
+### Download the test AI models
+    1. bash scripts/test_model_download.sh, then "resnet-test.onnx" will be got in ./build
+    2. you can change to any other onnx files as your needs, or edit the download link in 
+	   "scripts/test_model_download.sh"
+
+## Parse the onnx model
+    note: subgraphs_ios.txt will be generated in future code, suppose we already have it as 
+    the example file now
+
+## Split the onnx model to subgraphs
+    1. edit the config path and model file path at ./scripts/extract_onnx.py 
+       e.g.: extract_onnx_lib.split_onnx_ios('./scripts/subgraphs_ios.txt','./resnet-test.onnx') 
+    2. python scripts/extract_onnx.py, after extraction done, the subgraphs will be saved 
+	   at './subgraphs'
+       subgraphs
+       ├── CPU
+       │   ├── CPUsubgraph0.onnx
+       │   └── CPUsubgraph1.onnx
+       └── NPU
+           ├── NPUsubgraph0.onnx
+           └── NPUsubgraph1.onnx

tools/onnx-subgraph/extract_onnx.py

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+# Copyright (c) 2025 Samsung Electronics Co., Ltd. All Rights Reserved
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import onnx
+import re
+import os
+
+def splitsubgraph_ios(iofile):
+    iolist = re.split('--input-name |;--output-name ', iofile)
+    in_ = iolist[1].split(';')
+    out_ = iolist[2].split(';')
+    del out_[-1]
+    type = iolist[0].split('subgraph')[0]
+    return in_, out_, type
+
+def split_onnx_ios(instrfile,
+                   input_path='./resnet-test.onnx',
+                   out_folder='subgraphs/'):
+    if not os.path.exists(input_path):
+        print(input_path + " not exist")
+        return
+
+    model = onnx.load(input_path)
+    onnx.checker.check_model(input_path)
+    for output in model.graph.output:
+        model.graph.value_info.append(output)
+    onnx.save(model, input_path)
+    f1 = open(instrfile, "r")
+    lines = f1.readlines()
+    cpu_count = 0
+    npu_count = 0
+    count = 0
+    if not os.path.exists(out_folder):
+        os.makedirs(out_folder)
+    for line in lines:
+        input_names, output_names, type = splitsubgraph_ios(line)
+        if (type == 'CPU'):
+            count = cpu_count
+            cpu_count = cpu_count + 1
+        else:
+            count = npu_count
+            npu_count = npu_count + 1
+        output_path_folder = out_folder
+        if not os.path.exists(output_path_folder):
+            os.makedirs(output_path_folder)
+        output_path = output_path_folder + type + 'subgraph' + str(count) + '.onnx'
+        if ((input_names != ['']) and (output_names != [''])):
+            onnx.utils.extract_model(input_path, output_path, input_names, output_names)
+            print("succeed", count)
+            count = count + 1
+    f1.close()
+
+if __name__ == "__main__":
+    split_onnx_ios('./scripts/subgraphs_ios.txt', './resnet-test.onnx')

tools/onnx-subgraph/subgraphs_ios.txt

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+NPUsubgraph0: order0--input-name x;--output-name /stem/conv3/bn/act/Mul_output_0;
+NPUsubgraph1: order2--input-name /stem/pool/MaxPool_output_0;--output-name /stages/stages.3/stages.3.1/act/Mul_output_0;
+CPUsubgraph0: order1--input-name /stem/conv3/bn/act/Mul_output_0;--output-name /stem/pool/MaxPool_output_0;
+CPUsubgraph1: order3--input-name /stages/stages.3/stages.3.1/act/Mul_output_0;--output-name 316;

tools/onnx-subgraph/test_model_download.sh

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+pip install onnx onnxsim
+
+if [ ! -d "./models/" ];then
+  mkdir ./models/
+  else
+  echo "./models path existing"
+fi
+
+cd ./models
+wget https://media.githubusercontent.com/media/onnx/models/refs/heads/main/Computer_Vision/resnext26ts_Opset16_timm/resnext26ts_Opset16.onnx --no-check-certificate
+#wget https://media.githubusercontent.com/media/onnx/models/refs/heads/main/Natural_Language_Processing/xmod_Opset16_transformers/xmod_Opset16.onnx --no-check-certificate
+
+onnxsim resnext26ts_Opset16.onnx ../resnet-test.onnx
+#onnxsim xmod_Opset16.onnx ../xmod-transformer-test.onnx
+
+cd ..