# 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:
      - ".azure/gpu-benchmarks.yml"
      - "requirements/fabric/**"
      - "requirements/pytorch/**"
      - "src/lightning/fabric/**"
      - "src/lightning/pytorch/**"
      - "tests/parity_fabric/**"
      - "tests/parity_pytorch/**"
    exclude:
      - "requirements/*/docs.txt"
      - "*.md"
      - "**/*.md"

schedules:
  - cron: "0 0 * * *" # At the end of every day
    displayName: Daily midnight benchmark
    branches:
      include:
        - "master"

jobs:
  - job: benchmarks
    timeoutInMinutes: "90"
    cancelTimeoutInMinutes: "2"
    pool: lit-rtx-3090
    variables:
      DEVICES: $( python -c 'print("$(Agent.Name)".split("_")[-1])' )
    container:
      image: "pytorchlightning/pytorch_lightning:base-cuda-py3.10-torch2.0-cuda11.8.0"
      options: "--gpus=all --shm-size=32g"
    strategy:
      matrix:
        'pkg: Fabric':
          PACKAGE_NAME: "fabric"
        'pkg: Pytorch':
          PACKAGE_NAME: "pytorch"
    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=TORCH_URL]https://download.pytorch.org/whl/cu${cuda_ver}/torch_stable.html"
      displayName: 'set env. vars'

    - bash: |
        echo $CUDA_VISIBLE_DEVICES
        echo $TORCH_URL
        whereis nvidia
        nvidia-smi
        which python && which pip
        python --version
        pip --version
        pip list
      displayName: 'Image info & NVIDIA'

    - bash: pip install -e .[dev] --find-links ${TORCH_URL}
      env:
        FREEZE_REQUIREMENTS: "1"
      displayName: 'Install package'

    - bash: |
        set -e
        python requirements/collect_env_details.py
        python -c "import torch ; mgpu = torch.cuda.device_count() ; assert mgpu == 2, f'GPU: {mgpu}'"
      displayName: 'Env details'

    - bash: |
        pip install -q -r .actions/requirements.txt
        python .actions/assistant.py copy_replace_imports --source_dir="./tests" \
          --source_import="lightning.fabric,lightning.pytorch" \
          --target_import="lightning_fabric,pytorch_lightning"
      displayName: 'Adjust tests'

    - bash: python -m pytest parity_$(PACKAGE_NAME) -v --durations=0
      env:
        PL_RUNNING_BENCHMARKS: "1"
        PL_RUN_CUDA_TESTS: "1"
      workingDirectory: tests/
      displayName: 'Testing: benchmarks'

    - bash: bash run_standalone_tasks.sh
      workingDirectory: tests/parity_fabric
      # without succeeded this could run even if the job has already failed
      condition: and(succeeded(), eq(variables['PACKAGE_NAME'], 'fabric'))
      env:
        PL_RUN_CUDA_TESTS: "1"
      displayName: 'Testing: fabric standalone tasks'
      timeoutInMinutes: "10"