[Fix] fix the onnx exportation for yoloxpose in mmpose #4784
Workflow file for this run
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: backend-ncnn | |
| on: | |
| push: | |
| paths-ignore: | |
| - "demo/**" | |
| - "tools/**" | |
| pull_request: | |
| paths-ignore: | |
| - "demo/**" | |
| - "tools/**" | |
| - "docs/**" | |
| concurrency: | |
| group: ${{ github.workflow }}-${{ github.ref }} | |
| cancel-in-progress: true | |
| jobs: | |
| test_onnx2ncnn: | |
| runs-on: ubuntu-20.04 | |
| strategy: | |
| matrix: | |
| python-version: [3.7] | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@v3 | |
| with: | |
| submodules: 'recursive' | |
| - name: Set up Python ${{ matrix.python-version }} | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Install dependencies | |
| run: | | |
| sudo apt update | |
| sudo apt install wget gcc-multilib g++-multilib wget libprotobuf-dev protobuf-compiler | |
| python -m pip install cmake onnx | |
| - name: Install ncnn | |
| run: | | |
| wget https://github.com/Tencent/ncnn/archive/refs/tags/20220420.tar.gz | |
| tar xf 20220420.tar.gz | |
| pushd ncnn-20220420 | |
| mkdir build && pushd build | |
| cmake -DCMAKE_INSTALL_PREFIX=$(pwd)/../install -DNCNN_BUILD_TESTS=OFF -DNCNN_BUILD_TOOLS=OFF -DNCNN_BUILD_EXAMPLES=OFF .. | |
| cmake --build . -j2 | |
| make install | |
| popd && popd | |
| - name: Install mmdeploy with ncnn backend | |
| run: | | |
| mkdir -p build && pushd build | |
| export LD_LIBRARY_PATH=/home/runner/work/mmdeploy/mmdeploy/ncnn-20220420/install/lib/:$LD_LIBRARY_PATH | |
| cmake -DMMDEPLOY_TARGET_BACKENDS=ncnn -Dncnn_DIR=/home/runner/work/mmdeploy/mmdeploy/ncnn-20220420/install/lib/cmake/ncnn/ .. | |
| make mmdeploy_onnx2ncnn -j2 | |
| popd | |
| - name: Test onnx2ncnn | |
| run: | | |
| echo $(pwd) | |
| ln -s build/bin/mmdeploy_onnx2ncnn ./ | |
| python .github/scripts/test_onnx2ncnn.py --run 1 | |
| build_ncnn: | |
| runs-on: ubuntu-20.04 | |
| strategy: | |
| matrix: | |
| python-version: [3.7] | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@v3 | |
| with: | |
| submodules: 'recursive' | |
| - name: Set up Python ${{ matrix.python-version }} | |
| uses: actions/setup-python@v2 | |
| with: | |
| python-version: ${{ matrix.python-version }} | |
| - name: Install mmdeploy | |
| run: | | |
| python -m pip install torch==1.8.2 torchvision==0.9.2 --extra-index-url https://download.pytorch.org/whl/lts/1.8/cpu | |
| python -m pip install mmcv-lite | |
| python tools/scripts/build_ubuntu_x64_ncnn.py 8 | |
| python -c 'import mmdeploy.apis.ncnn as ncnn_api; assert ncnn_api.is_available(with_custom_ops=True)' | |
| test_ncnn_ptq: | |
| runs-on: [self-hosted, linux-3090] | |
| container: | |
| image: openmmlab/mmdeploy:ubuntu20.04-cuda11.3 | |
| options: "--gpus=all --ipc=host" | |
| steps: | |
| - name: Checkout repository | |
| uses: actions/checkout@v3 | |
| with: | |
| submodules: recursive | |
| - name: Install dependencies | |
| run: | | |
| apt-get update | |
| apt-get install ninja-build -y | |
| python3 -V | |
| python3 -m pip install openmim | |
| python3 -m pip install -r requirements.txt | |
| python3 -m mim install $(cat requirements/codebases.txt | grep mmpretrain) | |
| python3 -m pip install numpy==1.22.0 | |
| python3 -m pip list | |
| - name: Install mmdeploy | |
| run: | | |
| rm -rf .eggs && python3 -m pip install -e . | |
| python3 tools/check_env.py | |
| - name: Install ppq | |
| run: | | |
| git clone -b v0.6.6 --depth 1 https://github.com/openppl-public/ppq | |
| cd ppq | |
| python3 -m pip install -r requirements.txt | |
| python3 setup.py install | |
| - name: Test ncnn + ppq pipeline | |
| run: | | |
| export PYTHONPATH=${PWD}/ppq:${PYTHONPATH} | |
| export LD_LIBRARY_PATH="/root/workspace/mmdeploy/build/lib:${LD_LIBRARY_PATH}" | |
| export LD_LIBRARY_PATH="/root/workspace/mmdeploy/mmdeploy/lib:${LD_LIBRARY_PATH}" | |
| export work_dir=./work_dir | |
| mkdir -p $work_dir | |
| export model_cfg=$work_dir/resnet18_8xb32_in1k.py | |
| export deploy_cfg=configs/mmpretrain/classification_ncnn-int8_static.py | |
| export checkpoint=$work_dir/resnet18_8xb32_in1k_20210831-fbbb1da6.pth | |
| export input_img=tests/data/tiger.jpeg | |
| python3 -m mim download mmpretrain --config resnet18_8xb32_in1k --dest $work_dir | |
| python3 tools/torch2onnx.py $deploy_cfg $model_cfg $checkpoint $input_img --work-dir $work_dir | |
| wget https://github.com/open-mmlab/mmdeploy/releases/download/v0.1.0/dataset.tar | |
| tar xvf dataset.tar | |
| python3 tools/onnx2ncnn_quant_table.py \ | |
| --onnx $work_dir/end2end.onnx \ | |
| --deploy-cfg $deploy_cfg \ | |
| --model-cfg $model_cfg \ | |
| --out-onnx $work_dir/quant.onnx \ | |
| --out-table $work_dir/ncnn.table \ | |
| --image-dir ./dataset | |
| ls -sha $work_dir/quant.onnx | |
| cat $work_dir/ncnn.table |