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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

    cd onnx-subgraph
    mkdir build & cd build
    cmake .. & make
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

    python scripts/extract_onnx.py \
              -s ./scripts/subgraphs_ios.txt \
              -m ./resnet-test.onnx
after extraction done, the subgraphs will be saved at './subgraphs'

    subgraphs
    ├── CPUsubgraph0.onnx
    └── CPUsubgraph1.onnx
    ├── NPUsubgraph0.onnx
    └── NPUsubgraph1.onnx