# https://docs.drone.io/pipeline/docker/examples/languages/python/#python-example kind: pipeline type: docker name: torch-GPU steps: - name: testing image: pytorchlightning/pytorch_lightning:devel-pt1.4 environment: SLURM_LOCALID: 0 CODECOV_TOKEN: from_secret: codecov_token HOROVOD_GPU_ALLREDUCE: NCCL HOROVOD_GPU_BROADCAST: NCCL HOROVOD_WITH_PYTORCH: 1 HOROVOD_WITHOUT_TENSORFLOW: 1 HOROVOD_WITHOUT_MXNET: 1 HOROVOD_WITH_GLOO: 1 HOROVOD_WITHOUT_MPI: 1 #volumes: # # Mount pip cache from host # - name: pip_cache # path: /opt/conda/lib/python3.7/site-packages commands: - export PATH="$PATH:/root/.local/bin" - python --version - pip install pip -U - pip --version - nvidia-smi #- bash ./tests/install_AMP.sh - apt-get update && apt-get install -y cmake - pip install -r ./requirements/base.txt --user -q - pip install -r ./requirements/devel.txt --user -q #- pip install -r ./requirements/docs.txt --user -q - pip install -r ./requirements/examples.txt --user -q - pip list - python -c "import torch ; print(' & '.join([torch.cuda.get_device_name(i) for i in range(torch.cuda.device_count())]) if torch.cuda.is_available() else 'only CPU')" - coverage run --source pytorch_lightning -m py.test pytorch_lightning tests -v --durations=25 # --flake8 - python -m py.test benchmarks pl_examples -v --maxfail=2 --durations=0 # --flake8 #- cd docs; make doctest; make coverage - coverage report # see: https://docs.codecov.io/docs/merging-reports - codecov --token $CODECOV_TOKEN --flags=gpu,pytest --name="GPU-coverage" --env=linux --build $DRONE_BUILD_NUMBER --commit $DRONE_COMMIT # --build $DRONE_BUILD_NUMBER --branch $DRONE_BRANCH --commit $DRONE_COMMIT --tag $DRONE_TAG --pr $DRONE_PULL_REQUEST # - codecov --token $CODECOV_TOKEN --flags=gpu,pytest --build $DRONE_BUILD_NUMBER - python tests/collect_env_details.py trigger: branch: - master event: include: - push - pull_request #volumes: # - name: pip_cache # host: # path: /tmp/cache/drone/pip