lightning/.drone.yml

61 lines
1.8 KiB
YAML

# 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-pt_1_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
- codecov --token $CODECOV_TOKEN # --pr $DRONE_PULL_REQUEST --build $DRONE_BUILD_NUMBER --branch $DRONE_BRANCH --commit $DRONE_COMMIT --tag $DRONE_TAG
- python tests/collect_env_details.py
trigger:
branch:
- master
event:
include:
- push
- pull_request
#volumes:
# - name: pip_cache
# host:
# path: /tmp/cache/drone/pip