221 lines
9.0 KiB
YAML
221 lines
9.0 KiB
YAML
# Python package
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# Create and test a Python package on multiple Python versions.
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# Add steps that analyze code, save the dist with the build record, publish to a PyPI-compatible index, and more:
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# https://docs.microsoft.com/azure/devops/pipelines/languages/python
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trigger:
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tags:
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include: ["*"]
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branches:
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include:
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- "master"
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- "release/*"
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- "refs/tags/*"
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pr:
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branches:
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include:
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- "master"
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- "release/*"
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paths:
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include:
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- ".actions/*"
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- ".azure/gpu-tests-pytorch.yml"
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- "examples/run_pl_examples.sh"
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- "examples/pytorch/basics/backbone_image_classifier.py"
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- "examples/pytorch/basics/autoencoder.py"
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- "requirements/pytorch/**"
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- "src/lightning/__about__.py"
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- "src/lightning/__init__.py"
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- "src/lightning/__main__.py"
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- "src/lightning/__setup__.py"
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- "src/lightning/__version__.py"
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- "src/lightning/pytorch/**"
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- "src/pytorch_lightning/*"
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- "tests/tests_pytorch/**"
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- "pyproject.toml" # includes pytest config
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- "requirements/fabric/**"
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- "src/lightning/fabric/**"
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- "src/lightning_fabric/*"
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exclude:
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- "requirements/*/docs.txt"
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- "*.md"
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- "**/*.md"
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jobs:
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- job: testing
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# how long to run the job before automatically cancelling
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timeoutInMinutes: "80"
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# how much time to give 'run always even if cancelled tasks' before stopping them
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cancelTimeoutInMinutes: "2"
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strategy:
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matrix:
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"PyTorch | latest":
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image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
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IS_NIGHTLY: "false"
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PACKAGE_NAME: "pytorch"
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"Lightning | latest":
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image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
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IS_NIGHTLY: "false"
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PACKAGE_NAME: "lightning"
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"Lightning | RC":
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image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
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IS_NIGHTLY: "true"
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PACKAGE_NAME: "lightning"
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pool: lit-rtx-3090
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variables:
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DEVICES: $( python -c 'print("$(Agent.Name)".split("_")[-1])' )
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FREEZE_REQUIREMENTS: "1"
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PIP_CACHE_DIR: "/var/tmp/pip"
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container:
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image: $(image)
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# default shm size is 64m. Increase it to avoid:
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# 'Error while creating shared memory: unhandled system error, NCCL version 2.7.8'
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options: "--gpus=all --shm-size=2gb -v /var/tmp:/var/tmp"
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workspace:
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clean: all
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steps:
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- bash: |
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echo "##vso[task.setvariable variable=CUDA_VISIBLE_DEVICES]$(DEVICES)"
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cuda_ver=$(python -c "import torch ; print(''.join(map(str, torch.version.cuda.split('.')[:2])))")
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echo "##vso[task.setvariable variable=CUDA_VERSION_MM]$cuda_ver"
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echo "##vso[task.setvariable variable=TORCH_URL]https://download.pytorch.org/whl/cu${cuda_ver}/torch_stable.html"
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scope=$(python -c 'n = "$(PACKAGE_NAME)" ; print(dict(pytorch="pytorch_lightning").get(n, n))')
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echo "##vso[task.setvariable variable=COVERAGE_SOURCE]$scope"
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displayName: "set env. vars"
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- bash: |
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echo $(DEVICES)
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echo $CUDA_VISIBLE_DEVICES
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echo $CUDA_VERSION_MM
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echo $TORCH_URL
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echo $(IS_NIGHTLY)
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echo $COVERAGE_SOURCE
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whereis nvidia
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nvidia-smi
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which python && which pip
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python --version
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pip --version
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pip list
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displayName: "Image info & NVIDIA"
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- bash: |
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PYTORCH_VERSION=$(python -c "import torch; print(torch.__version__.split('+')[0])")
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pip install -q wget packaging
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python -m wget https://raw.githubusercontent.com/Lightning-AI/utilities/main/scripts/adjust-torch-versions.py
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for fpath in `ls requirements/**/*.txt`; do \
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python ./adjust-torch-versions.py $fpath ${PYTORCH_VERSION}; \
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done
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables.IS_NIGHTLY, 'false'))
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displayName: "Adjust dependencies"
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- bash: |
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pip install -q -r .actions/requirements.txt
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python .actions/assistant.py requirements_prune_pkgs \
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--packages="[lightning-colossalai,lightning-bagua]" \
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--req_files="[requirements/_integrations/strategies.txt]"
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displayName: "Prune packages" # these have installation issues
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- bash: |
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extra=$(python -c "print({'lightning': 'pytorch-'}.get('$(PACKAGE_NAME)', ''))")
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pip install -e ".[${extra}dev]" -r requirements/_integrations/strategies.txt pytest-timeout -U --find-links ${TORCH_URL}
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displayName: "Install package & dependencies"
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- bash: |
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pip uninstall -y torch torchvision
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pip install torch torchvision -U --pre --no-cache --index-url https://download.pytorch.org/whl/test/cu${CUDA_VERSION_MM%}
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python -c "from torch import __version__ as ver; assert ver.startswith('2.1.0'), ver"
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables.IS_NIGHTLY, 'true'))
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displayName: "Bump to RC"
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- bash: pip uninstall -y lightning
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
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# Lightning is dependency of Habana or other accelerators/integrations so in case we test PL we need to remove it
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displayName: "Drop LAI from extensions"
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- bash: pip uninstall -y pytorch-lightning
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'lightning'))
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displayName: "Drop PL for LAI"
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- bash: |
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set -e
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python requirements/collect_env_details.py
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python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu == 2, f'GPU: {mgpu}'"
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python requirements/pytorch/check-avail-extras.py
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displayName: "Env details"
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- bash: python -m pytest pytorch_lightning
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workingDirectory: src
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
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displayName: "Testing: PyTorch doctests"
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- bash: |
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python .actions/assistant.py copy_replace_imports --source_dir="./tests/tests_pytorch" \
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--source_import="lightning.fabric,lightning.pytorch" \
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--target_import="lightning_fabric,pytorch_lightning"
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python .actions/assistant.py copy_replace_imports --source_dir="./examples/pytorch/basics" \
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--source_import="lightning.fabric,lightning.pytorch" \
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--target_import="lightning_fabric,pytorch_lightning"
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# without succeeded this could run even if the job has already failed
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condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
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displayName: "Adjust tests & examples"
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- bash: |
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bash .actions/pull_legacy_checkpoints.sh
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cd tests/legacy
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bash generate_checkpoints.sh
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ls -l checkpoints/
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displayName: "Get legacy checkpoints"
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- bash: python -m coverage run --source ${COVERAGE_SOURCE} -m pytest -v --durations=50
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workingDirectory: tests/tests_pytorch
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env:
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PL_RUN_CUDA_TESTS: "1"
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displayName: "Testing: PyTorch standard"
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timeoutInMinutes: "35"
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- bash: bash run_standalone_tests.sh
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workingDirectory: tests/tests_pytorch
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env:
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PL_USE_MOCKED_MNIST: "1"
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PL_RUN_CUDA_TESTS: "1"
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PL_STANDALONE_TESTS_SOURCE: $(COVERAGE_SOURCE)
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displayName: "Testing: PyTorch standalone tests"
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timeoutInMinutes: "35"
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- bash: bash run_standalone_tasks.sh
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workingDirectory: tests/tests_pytorch
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env:
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PL_USE_MOCKED_MNIST: "1"
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PL_RUN_CUDA_TESTS: "1"
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displayName: "Testing: PyTorch standalone tasks"
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timeoutInMinutes: "10"
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- bash: |
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python -m coverage report
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python -m coverage xml
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python -m coverage html
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# https://docs.codecov.com/docs/codecov-uploader
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curl -Os https://uploader.codecov.io/latest/linux/codecov
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chmod +x codecov
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./codecov --token=$(CODECOV_TOKEN) --commit=$(Build.SourceVersion) \
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--flags=gpu,pytest,${COVERAGE_SOURCE} --name="GPU-coverage" --env=linux,azure
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ls -l
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workingDirectory: tests/tests_pytorch
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displayName: "Statistics"
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- script: |
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set -e
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bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=1
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bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=2 --trainer.strategy=ddp
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bash run_pl_examples.sh --trainer.accelerator=gpu --trainer.devices=2 --trainer.strategy=ddp --trainer.precision=16
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workingDirectory: examples
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env:
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PL_USE_MOCKED_MNIST: "1"
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displayName: "Testing: PyTorch examples"
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