59 lines
1.7 KiB
YAML
59 lines
1.7 KiB
YAML
# https://docs.drone.io/pipeline/docker/examples/languages/python/#python-example
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kind: pipeline
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type: docker
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name: torch-GPU
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steps:
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- name: testing
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image: pytorchlightning/pytorch_lightning:devel-pt_1_4
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environment:
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SLURM_LOCALID: 0
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CODECOV_TOKEN:
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from_secret: codecov_token
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HOROVOD_GPU_ALLREDUCE: NCCL
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HOROVOD_GPU_BROADCAST: NCCL
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HOROVOD_WITH_PYTORCH: 1
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HOROVOD_WITHOUT_TENSORFLOW: 1
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HOROVOD_WITHOUT_MXNET: 1
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HOROVOD_WITH_GLOO: 1
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HOROVOD_WITHOUT_MPI: 1
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#volumes:
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# # Mount pip cache from host
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# - name: pip_cache
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# path: /opt/conda/lib/python3.7/site-packages
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commands:
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- export PATH="$PATH:/root/.local/bin"
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- python --version
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- pip install pip -U
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- pip --version
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- nvidia-smi
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#- bash ./tests/install_AMP.sh
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- apt-get update && apt-get install -y cmake
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- pip install -r requirements.txt --user -q
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- pip install -r ./tests/requirements-devel.txt --user -q
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#- pip install -r ./docs/requirements.txt --user -q
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- pip list
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- 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')"
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- coverage run --source pytorch_lightning -m py.test pytorch_lightning tests benchmarks -v --doctest-modules # --flake8
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#- cd docs; make doctest; make coverage
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- coverage report
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- codecov --token $CODECOV_TOKEN # --pr $DRONE_PULL_REQUEST --build $DRONE_BUILD_NUMBER --branch $DRONE_BRANCH --commit $DRONE_COMMIT --tag $DRONE_TAG
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- python tests/collect_env_details.py
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trigger:
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branch:
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- master
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event:
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include:
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- push
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- pull_request
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#volumes:
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# - name: pip_cache
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# host:
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# path: /tmp/cache/drone/pip
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