# Copyright The PyTorch Lightning team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # 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:base-cuda-py3.7-torch1.6 environment: CODECOV_TOKEN: from_secret: codecov_token MKL_THREADING_LAYER: GNU commands: - python --version - pip --version - nvidia-smi - pip install -r ./requirements/devel.txt --upgrade-strategy only-if-needed -v --no-cache-dir # when Image has defined CUDa version we can switch to this package spec "nvidia-dali-cuda${CUDA_VERSION%%.*}0" - pip install --extra-index-url https://developer.download.nvidia.com/compute/redist nvidia-dali-cuda100 --upgrade-strategy only-if-needed - pip list - coverage run --source pytorch_lightning -m pytest pytorch_lightning tests -v --durations=25 # --flake8 - python -m pytest 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 - release/* event: include: - push - pull_request