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# https://docs.drone.io/pipeline/docker/examples/languages/python/#python-example
kind : pipeline
type : docker
name : torch-GPU
steps :
- name : testing
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image : pytorchlightning/pytorch_lightning:devel-pt1.4
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environment :
SLURM_LOCALID : 0
CODECOV_TOKEN :
from_secret : codecov_token
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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
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#volumes:
# # Mount pip cache from host
# - name: pip_cache
# 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
- pip install pip -U
- pip --version
- 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/base.txt --user -q
- pip install -r ./requirements/devel.txt --user -q
#- pip install -r ./requirements/docs.txt --user -q
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- pip install -r ./requirements/examples.txt --user -q
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- 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')"
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- 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
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#- cd docs; make doctest; make coverage
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- coverage report
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# see: https://docs.codecov.io/docs/merging-reports
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- codecov --token $CODECOV_TOKEN --flags=gpu,pytest --name="GPU-coverage" --env=linux --build $DRONE_BUILD_NUMBER --commit $DRONE_COMMIT
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# --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
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- python tests/collect_env_details.py
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trigger :
branch :
- master
event :
include :
- push
- pull_request
#volumes:
# - name: pip_cache
# host:
# path: /tmp/cache/drone/pip