mirror of https://github.com/open-mmlab/mmcv.git
174 lines
5.9 KiB
YAML
174 lines
5.9 KiB
YAML
version: 2.1
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jobs:
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lint:
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docker:
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- image: cimg/python:3.7.4
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steps:
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- checkout
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- run:
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name: Install pre-commit hook
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command: |
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pip install pre-commit
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pre-commit install
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- run:
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name: Linting
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command: pre-commit run --all-files
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build_cpu:
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parameters:
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# The python version must match available image tags in
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# https://circleci.com/developer/images/image/cimg/python
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python:
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type: string
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default: "3.7.0"
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torch:
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type: string
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torchvision:
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type: string
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machine:
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image: ubuntu-2004:202010-01
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resource_class: large
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steps:
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- checkout
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- run:
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name: Install system dependencies
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command: |
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sudo apt-get update
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sudo apt-get install -y ffmpeg libturbojpeg ninja-build
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ffmpeg -version
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- run:
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# https://github.com/pytorch/vision/issues/2921
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name: Install dependency of torchvision when using pyenv
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command: sudo apt-get install -y liblzma-dev
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- run:
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# python3.7 should be re-installed due to the issue https://github.com/pytorch/vision/issues/2921
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name: Select Python
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command: |
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pyenv uninstall -f << parameters.python >>
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pyenv install << parameters.python >>
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pyenv global << parameters.python >>
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- run:
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name: Upgrade pip
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command: |
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python -m pip install pip --upgrade
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- run:
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name: Install PyTorch
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command: python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
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- run:
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name: Install psutil
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command: python -m pip install psutil
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- run:
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name: Build and install
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command: |
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rm -rf .eggs
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python setup.py check -m -s
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python -m pip install -e .
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no_output_timeout: 20m
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environment:
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MMCV_WITH_OPS: 1
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- run:
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name: Install dependencies of unit test
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command: |
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python -m pip install -r requirements/test.txt
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- run:
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name: Run unittests and generate coverage report
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command: |
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python -m coverage run --branch --source mmcv -m pytest tests/
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python -m coverage xml
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python -m coverage report -m
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build_cu102:
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machine:
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image: ubuntu-1604-cuda-10.1:201909-23 # the actual version of cuda is 10.2
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resource_class: gpu.nvidia.small
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steps:
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- checkout
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- run:
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name: Set CUDA environment
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command: |
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echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> $BASH_ENV
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echo 'export PATH=/usr/local/cuda/bin:$PATH' >> $BASH_ENV
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echo 'export CUDA_HOME=/usr/local/cuda' >> $BASH_ENV
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source $BASH_ENV
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nvidia-smi
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nvcc --version
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gcc --version
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- run:
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name: Install system dependencies
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command: |
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sudo apt-get update
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sudo apt-get install -y libturbojpeg ninja-build
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# the default version of ffmpeg is 2.8.7, which should be upgraded to 4+
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sudo add-apt-repository -y ppa:jonathonf/ffmpeg-4
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sudo apt-get update
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sudo apt-get install -y ffmpeg
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ffmpeg -version
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sudo add-apt-repository --remove ppa:jonathonf/ffmpeg-4 -y
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- run:
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# https://github.com/pytorch/vision/issues/2921
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name: Install dependency of torchvision when using pyenv
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command: sudo apt-get install -y liblzma-dev
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- run:
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# python3.7 should be re-installed due to the issue https://github.com/pytorch/vision/issues/2921
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name: Select python3.7
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command: |
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pyenv uninstall -f 3.7.0
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pyenv install 3.7.0
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pyenv global 3.7.0
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- run:
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name: Upgrade pip
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command: |
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python -m pip install pip --upgrade
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- run:
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name: Install PyTorch
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command: python -m pip install torch==1.8.1+cu102 torchvision==0.9.1+cu102 -f https://download.pytorch.org/whl/torch_stable.html
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- run:
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name: Install psutil
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command: python -m pip install psutil
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- run:
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name: Download onnxruntime library and install onnxruntime
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command: |
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wget https://github.com/microsoft/onnxruntime/releases/download/v1.8.1/onnxruntime-linux-x64-1.8.1.tgz
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tar -zxvf onnxruntime-linux-x64-1.8.1.tgz
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echo 'export ONNXRUNTIME_DIR=$(pwd)/onnxruntime-linux-x64-1.8.1' >> $BASH_ENV
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echo 'export LD_LIBRARY_PATH=$ONNXRUNTIME_DIR/lib:$LD_LIBRARY_PATH' >> $BASH_ENV
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source $BASH_ENV
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python -m pip install onnxruntime==1.8.1
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- run:
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name: Build and install
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command: |
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rm -rf .eggs
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python setup.py check -m -s
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python -m pip install -e .
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environment:
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MMCV_WITH_OPS: 1
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MMCV_WITH_ORT: 1
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- run:
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name: Install dependencies for unit test
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command: |
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python -m pip install -r requirements/test.txt
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- run:
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name: Run unittests and generate coverage report
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command: |
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python -m coverage run --branch --source mmcv -m pytest tests/
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python -m coverage xml
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python -m coverage report -m
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workflows:
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unit_tests:
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jobs:
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- lint
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- build_cpu:
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name: build_py3.8_pt1.9_cpu
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torch: 1.9.0
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torchvision: 0.10.0
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python: "3.8.0"
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requires:
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- lint
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- hold:
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type: approval # <<< This key-value pair will set your workflow to a status of "On Hold"
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requires:
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- build_py3.8_pt1.9_cpu
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- build_cu102:
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requires:
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- hold
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