# Python package # Create and test a Python package on multiple Python versions. # Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more: # https://docs.microsoft.com/azure/devops/pipelines/languages/python trigger: tags: include: - '*' branches: include: - "master" - "release/*" - "refs/tags/*" pr: branches: include: - "master" - "release/*" paths: include: - ".actions/**" - ".azure/gpu-tests-pytorch.yml" - "examples/run_pl_examples.sh" - "examples/pl_basics/backbone_image_classifier.py" - "examples/pl_basics/autoencoder.py" - "examples/pl_fault_tolerant/automatic.py" - "requirements/pytorch/**" - "src/pytorch_lightning/**" - "tests/tests_pytorch/**" - "setup.cfg" # includes pytest config - "requirements/fabric/**" - "src/lightning_fabric/**" exclude: - "requirements/*/docs.txt" - "*.md" - "**/*.md" jobs: - job: testing strategy: matrix: 'PyTorch & strategies': # this uses torch 1.12 as not all strategies support 1.13 yet image: "pytorchlightning/pytorch_lightning:base-cuda-py3.9-torch1.12-cuda11.6.1" scope: "strategies" 'PyTorch - latest': image: "pytorchlightning/pytorch_lightning:base-cuda-py3.9-torch1.13-cuda11.7.1" scope: "" # how long to run the job before automatically cancelling timeoutInMinutes: "80" # how much time to give 'run always even if cancelled tasks' before stopping them cancelTimeoutInMinutes: "2" pool: lit-rtx-3090 variables: DEVICES: $( python -c 'print("$(Agent.Name)".split("_")[-1])' ) container: image: $(image) # default shm size is 64m. Increase it to avoid: # 'Error while creating shared memory: unhandled system error, NCCL version 2.7.8' options: "--gpus=all --shm-size=2gb" workspace: clean: all steps: - bash: | echo "##vso[task.setvariable variable=CUDA_VISIBLE_DEVICES]$(DEVICES)" cuda_ver=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda.split('.')[:2])))") echo "##vso[task.setvariable variable=CUDA_VERSION_MM]$cuda_ver" echo "##vso[task.setvariable variable=TORCH_URL]https://download.pytorch.org/whl/cu${cuda_ver}/torch_stable.html" displayName: 'set env. vars' - bash: | echo $CUDA_VISIBLE_DEVICES echo $CUDA_VERSION_MM echo $TORCH_URL lspci | egrep 'VGA|3D' whereis nvidia nvidia-smi which python && which pip python --version pip --version pip list displayName: 'Image info & NVIDIA' - bash: | PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__.split('+')[0])") for fpath in `ls requirements/**/*.txt`; do \ python ./requirements/pytorch/adjust-versions.py $fpath ${PYTORCH_VERSION}; \ done displayName: 'Adjust dependencies' - bash: pip install -e .[extra,test,examples] --find-links ${TORCH_URL} env: PACKAGE_NAME: "pytorch" FREEZE_REQUIREMENTS: "1" displayName: 'Install package & extras' - bash: pip uninstall -y -r requirements/pytorch/strategies.txt condition: eq(variables['scope'], '') displayName: 'UnInstall strategies' - bash: | set -e CUDA_VERSION_BAGUA=$(python -c "print([ver for ver in [116,113,111,102] if $CUDA_VERSION_MM >= ver][0])") pip install "bagua-cuda$CUDA_VERSION_BAGUA" PYTORCH_VERSION_COLOSSALAI=$(python -c "import torch; print(torch.__version__.split('+')[0][:4])") CUDA_VERSION_MM_COLOSSALAI=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda)))") CUDA_VERSION_COLOSSALAI=$(python -c "print([ver for ver in [11.3, 11.1] if $CUDA_VERSION_MM_COLOSSALAI >= ver][0])") pip install "colossalai==0.1.10+torch${PYTORCH_VERSION_COLOSSALAI}cu${CUDA_VERSION_COLOSSALAI}" --find-links https://release.colossalai.org pip install -r requirements/pytorch/strategies.txt --find-links ${TORCH_URL} python requirements/pytorch/check-avail-strategies.py condition: eq(variables['scope'], 'strategies') displayName: 'Install strategies' - bash: | set -e pip list python requirements/collect_env_details.py python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu == 2, f'GPU: {mgpu}'" python requirements/pytorch/check-avail-extras.py displayName: 'Env details' - bash: bash .actions/pull_legacy_checkpoints.sh displayName: 'Get legacy checkpoints' - bash: python -m pytest pytorch_lightning workingDirectory: src displayName: 'Testing: PyTorch doctests' - bash: python -m coverage run --source pytorch_lightning -m pytest --ignore benchmarks -v --junitxml=$(Build.StagingDirectory)/test-results.xml --durations=50 env: PL_RUN_CUDA_TESTS: "1" workingDirectory: tests/tests_pytorch displayName: 'Testing: PyTorch standard' timeoutInMinutes: "35" - bash: bash run_standalone_tests.sh workingDirectory: tests/tests_pytorch env: PL_USE_MOCKED_MNIST: "1" PL_RUN_CUDA_TESTS: "1" PL_STANDALONE_TESTS_SOURCE: "pytorch_lightning" displayName: 'Testing: PyTorch standalone tests' timeoutInMinutes: "35" - bash: bash run_standalone_tasks.sh workingDirectory: tests/tests_pytorch env: PL_USE_MOCKED_MNIST: "1" PL_RUN_CUDA_TESTS: "1" displayName: 'Testing: PyTorch standalone tasks' timeoutInMinutes: "10" - bash: | python -m coverage report python -m coverage xml python -m coverage html python -m codecov --token=$(CODECOV_TOKEN) --commit=$(Build.SourceVersion) --flags=gpu,pytest --name="GPU-coverage" --env=linux,azure ls -l workingDirectory: tests/tests_pytorch displayName: 'Statistics' - task: PublishTestResults@2 displayName: 'Publish test results' inputs: testResultsFiles: '$(Build.StagingDirectory)/test-results.xml' testRunTitle: '$(Agent.OS) - $(Build.DefinitionName) - Python $(python.version)' condition: succeededOrFailed() - script: | set -e bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=1 bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=2 --trainer.strategy=ddp bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=2 --trainer.strategy=ddp --trainer.precision=16 workingDirectory: examples env: PL_USE_MOCKED_MNIST: "1" displayName: 'Testing: PyTorch examples' - bash: python -m pytest benchmarks -v --maxfail=2 --durations=0 workingDirectory: tests/tests_pytorch env: PL_RUN_CUDA_TESTS: "1" displayName: 'Testing: PyTorch benchmarks'