# 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/pytorch/basics/backbone_image_classifier.py"
      - "examples/pytorch/basics/autoencoder.py"
      - "requirements/pytorch/**"
      - "src/lightning/__about__.py"
      - "src/lightning/__init__.py"
      - "src/lightning/__main__.py"
      - "src/lightning/__setup__.py"
      - "src/lightning/__version__.py"
      - "src/lightning/pytorch/**"
      - "src/pytorch_lightning/*"
      - "tests/tests_pytorch/**"
      - "pyproject.toml"  # includes pytest config
      - "requirements/fabric/**"
      - "src/lightning/fabric/**"
      - "src/lightning_fabric/*"
    exclude:
      - "requirements/*/docs.txt"
      - "*.md"
      - "**/*.md"

jobs:
  - job: testing
    # 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"
    strategy:
      matrix:
        'PyTorch | latest':
          image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
          IS_NIGHTLY: "false"
          PACKAGE_NAME: "pytorch"
        'Lightning | latest':
          image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
          IS_NIGHTLY: "false"
          PACKAGE_NAME: "lightning"
        'Lightning | nightly':
          image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
          IS_NIGHTLY: "true"
          PACKAGE_NAME: "lightning"
    pool: lit-rtx-3090
    variables:
      DEVICES: $( python -c 'print("$(Agent.Name)".split("_")[-1])' )
      FREEZE_REQUIREMENTS: "1"
      PIP_CACHE_DIR: "/var/tmp/pip"
    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  -v /var/tmp:/var/tmp"
    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"
        scope=$(python -c 'n = "$(PACKAGE_NAME)" ; print(dict(pytorch="pytorch_lightning").get(n, n))')
        echo "##vso[task.setvariable variable=COVERAGE_SOURCE]$scope"
      displayName: 'set env. vars'

    - bash: |
        echo $(DEVICES)
        echo $CUDA_VISIBLE_DEVICES
        echo $CUDA_VERSION_MM
        echo $TORCH_URL
        echo $(IS_NIGHTLY)
        echo $COVERAGE_SOURCE
        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])")
        pip install -q wget packaging
        python -m wget https://raw.githubusercontent.com/Lightning-AI/utilities/main/scripts/adjust-torch-versions.py
        for fpath in `ls requirements/**/*.txt`; do \
          python ./adjust-torch-versions.py $fpath ${PYTORCH_VERSION}; \
        done
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables.IS_NIGHTLY, 'false'))
      displayName: 'Adjust dependencies'

    - bash: |
        pip install -q -r .actions/requirements.txt
        python .actions/assistant.py requirements_prune_pkgs \
          --packages="[lightning-colossalai,lightning-bagua]" \
          --req_files="[requirements/_integrations/strategies.txt]"
      displayName: 'Prune packages'  # these have installation issues

    - bash: |
        extra=$(python -c "print({'lightning': 'pytorch-'}.get('$(PACKAGE_NAME)', ''))")
        pip install -e ".[${extra}dev]" -r requirements/_integrations/strategies.txt pytest-timeout -U --find-links ${TORCH_URL}
      displayName: 'Install package & dependencies'

    - bash: |
        pip uninstall -y torch torchvision
        pip install torch torchvision -U --pre --no-cache --index-url https://download.pytorch.org/whl/nightly/cu${CUDA_VERSION_MM%}
        python -c "from torch import __version__ as ver; assert ver.startswith('2.1.0'), ver"
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables.IS_NIGHTLY, 'true'))
      displayName: 'Bump to nightly'

    - bash: pip uninstall -y lightning
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
      # Lightning is dependency of Habana or other accelerators/integrations so in case we test PL we need to remove it
      displayName: 'Drop LAI from extensions'
    - bash: pip uninstall -y pytorch-lightning
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'lightning'))
      displayName: 'Drop PL for LAI'

    - bash: |
        set -e
        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: python -m pytest pytorch_lightning
      workingDirectory: src
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
      displayName: 'Testing: PyTorch doctests'

    - bash: |
        python .actions/assistant.py copy_replace_imports --source_dir="./tests/tests_pytorch" \
          --source_import="lightning.fabric,lightning.pytorch" \
          --target_import="lightning_fabric,pytorch_lightning"
        python .actions/assistant.py copy_replace_imports --source_dir="./examples/pytorch/basics" \
          --source_import="lightning.fabric,lightning.pytorch" \
          --target_import="lightning_fabric,pytorch_lightning"
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'pytorch'))
      displayName: 'Adjust tests & examples'

    - bash: |
        bash .actions/pull_legacy_checkpoints.sh
        cd tests/legacy
        bash generate_checkpoints.sh
        ls -l checkpoints/
      displayName: 'Get legacy checkpoints'

    - bash: python -m coverage run --source ${COVERAGE_SOURCE} -m pytest -v --durations=50
      workingDirectory: tests/tests_pytorch
      env:
        PL_RUN_CUDA_TESTS: "1"
      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: $(COVERAGE_SOURCE)
      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

        # https://docs.codecov.com/docs/codecov-uploader
        curl -Os https://uploader.codecov.io/latest/linux/codecov
        chmod +x codecov
        ./codecov --token=$(CODECOV_TOKEN) --commit=$(Build.SourceVersion) \
          --flags=gpu,pytest,${COVERAGE_SOURCE} --name="GPU-coverage" --env=linux,azure
        ls -l
      workingDirectory: tests/tests_pytorch
      displayName: 'Statistics'

    - 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'