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Running
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L40S
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version: 2.1
jobs:
lint:
docker:
- image: cimg/python:3.7.4
steps:
- checkout
- run:
name: Install pre-commit hook
command: |
pip install pre-commit
pre-commit install
- run:
name: Linting
command: pre-commit run --all-files
build_cpu:
parameters:
# The python version must match available image tags in
# https://circleci.com/developer/images/image/cimg/python
python:
type: string
default: "3.7.0"
torch:
type: string
torchvision:
type: string
machine:
image: ubuntu-2004:202010-01
resource_class: large
steps:
- checkout
- run:
name: Install system dependencies
command: |
sudo apt-get update
sudo apt-get install -y ffmpeg libturbojpeg ninja-build
ffmpeg -version
- run:
# https://github.com/pytorch/vision/issues/2921
name: Install dependency of torchvision when using pyenv
command: sudo apt-get install -y liblzma-dev
- run:
# python3.7 should be re-installed due to the issue https://github.com/pytorch/vision/issues/2921
name: Select Python
command: |
pyenv uninstall -f << parameters.python >>
pyenv install << parameters.python >>
pyenv global << parameters.python >>
- run:
name: Upgrade pip
command: |
python -m pip install pip --upgrade
- run:
name: Install PyTorch
command: python -m pip install torch==<< parameters.torch >>+cpu torchvision==<< parameters.torchvision >>+cpu -f https://download.pytorch.org/whl/torch_stable.html
- run:
name: Install psutil
command: python -m pip install psutil
- run:
name: Build and install
command: |
rm -rf .eggs
python setup.py check -m -s
python -m pip install -e .
no_output_timeout: 20m
environment:
MMCV_WITH_OPS: 1
- run:
name: Install dependencies of unit test
command: |
python -m pip install -r requirements/test.txt
- run:
name: Run unittests and generate coverage report
command: |
python -m coverage run --branch --source mmcv -m pytest tests/
python -m coverage xml
python -m coverage report -m
build_cu102:
machine:
image: ubuntu-1604-cuda-10.1:201909-23 # the actual version of cuda is 10.2
resource_class: gpu.nvidia.small
steps:
- checkout
- run:
name: Set CUDA environment
command: |
echo 'export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH' >> $BASH_ENV
echo 'export PATH=/usr/local/cuda/bin:$PATH' >> $BASH_ENV
echo 'export CUDA_HOME=/usr/local/cuda' >> $BASH_ENV
source $BASH_ENV
nvidia-smi
nvcc --version
gcc --version
- run:
name: Install system dependencies
command: |
sudo apt-get update
sudo apt-get install -y libturbojpeg ninja-build
# the default version of ffmpeg is 2.8.7, which should be upgraded to 4+
sudo add-apt-repository -y ppa:jonathonf/ffmpeg-4
sudo apt-get update
sudo apt-get install -y ffmpeg
ffmpeg -version
sudo add-apt-repository --remove ppa:jonathonf/ffmpeg-4 -y
- run:
# https://github.com/pytorch/vision/issues/2921
name: Install dependency of torchvision when using pyenv
command: sudo apt-get install -y liblzma-dev
- run:
# python3.7 should be re-installed due to the issue https://github.com/pytorch/vision/issues/2921
name: Select python3.7
command: |
pyenv uninstall -f 3.7.0
pyenv install 3.7.0
pyenv global 3.7.0
- run:
name: Upgrade pip
command: |
python -m pip install pip --upgrade
- run:
name: Install PyTorch
command: python -m pip install torch==1.8.1+cu102 torchvision==0.9.1+cu102 -f https://download.pytorch.org/whl/torch_stable.html
- run:
name: Install psutil
command: python -m pip install psutil
- run:
name: Download onnxruntime library and install onnxruntime
command: |
wget https://github.com/microsoft/onnxruntime/releases/download/v1.8.1/onnxruntime-linux-x64-1.8.1.tgz
tar -zxvf onnxruntime-linux-x64-1.8.1.tgz
echo 'export ONNXRUNTIME_DIR=$(pwd)/onnxruntime-linux-x64-1.8.1' >> $BASH_ENV
echo 'export LD_LIBRARY_PATH=$ONNXRUNTIME_DIR/lib:$LD_LIBRARY_PATH' >> $BASH_ENV
source $BASH_ENV
python -m pip install onnxruntime==1.8.1
- run:
name: Build and install
command: |
rm -rf .eggs
python setup.py check -m -s
python -m pip install -e .
environment:
MMCV_WITH_OPS: 1
MMCV_WITH_ORT: 1
- run:
name: Install dependencies for unit test
command: |
python -m pip install -r requirements/test.txt
- run:
name: Run unittests and generate coverage report
command: |
python -m coverage run --branch --source mmcv -m pytest tests/
python -m coverage xml
python -m coverage report -m
workflows:
unit_tests:
jobs:
- lint
- build_cpu:
name: build_py3.8_pt1.9_cpu
torch: 1.9.0
torchvision: 0.10.0
python: "3.8.0"
requires:
- lint
- hold:
type: approval # <<< This key-value pair will set your workflow to a status of "On Hold"
requires:
- build_py3.8_pt1.9_cpu
- build_cu102:
requires:
- hold
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