78 lines
2.3 KiB
YAML
78 lines
2.3 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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- '*'
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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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- ".azure/gpu-benchmark.yml"
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schedules:
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- cron: "0 0 * * *" # At the end of every day
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displayName: Daily midnight benchmark
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branches:
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include:
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- "master"
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jobs:
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- job: benchmarks
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timeoutInMinutes: "90"
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cancelTimeoutInMinutes: "2"
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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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container:
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image: "pytorchlightning/pytorch_lightning:base-cuda-py3.9-torch1.12-cuda11.6.1"
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options: "--gpus=all --shm-size=32g"
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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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displayName: 'set env. vars'
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- bash: |
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pip install -e . --find-links ${TORCH_URL}
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git checkout -- setup.py MANIFEST.in
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env:
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PACKAGE_NAME: lite
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FREEZE_REQUIREMENTS: 1
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# Lite shall have pin version, so to keep development aligned we need to install lite from source not from pypi
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# also installing from source not from on-the-fly created package tp prevent accidental interaction with cache
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displayName: 'Install Lite pkg'
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- bash: |
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pip install -e .[strategies] --find-links ${TORCH_URL}
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pip list
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env:
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PACKAGE_NAME: pytorch
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FREEZE_REQUIREMENTS: 1
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displayName: 'Install package'
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- bash: python -m pytest benchmarks -v --durations=0
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env:
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PL_RUNNING_BENCHMARKS: "1"
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PL_RUN_CUDA_TESTS: "1"
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workingDirectory: tests/tests_pytorch
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displayName: 'Testing: PyTorch benchmarks'
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