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Try add GPU ci for prototype transforms
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name: Prototype transforms unit-tests on Linux GPU
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on:
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pull_request:
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push:
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branches:
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- nightly
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- main
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- release/*
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workflow_dispatch:
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env:
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CHANNEL: "nightly"
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jobs:
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tests:
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strategy:
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matrix:
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python_version: ["3.8"]
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cuda_arch_version: ["11.6"]
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fail-fast: false
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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with:
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runner: linux.g5.4xlarge.nvidia.gpu
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repository: pytorch/vision
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gpu-arch-type: cuda
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gpu-arch-version: ${{ matrix.cuda_arch_version }}
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timeout: 120
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script: |
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# Mark Build Directory Safe
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git config --global --add safe.directory /__w/vision/vision
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# Set up Environment Variables
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export PYTHON_VERSION="${{ matrix.python_version }}"
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export VERSION="${{ matrix.cuda_arch_version }}"
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export CUDATOOLKIT="pytorch-cuda=${VERSION}"
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# Set CHANNEL
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if [[ (${GITHUB_EVENT_NAME} = 'pull_request' && (${GITHUB_BASE_REF} = 'release'*)) || (${GITHUB_REF} = 'refs/heads/release'*) ]]; then
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export CHANNEL=test
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else
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export CHANNEL=nightly
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fi
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# Create Conda Env
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conda create -yp ci_env python="${PYTHON_VERSION}" numpy libpng jpeg scipy
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conda activate /work/ci_env
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# Install PyTorch, Torchvision, and testing libraries
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set -ex
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conda install \
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--yes \
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-c "pytorch-${CHANNEL}" \
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-c nvidia "pytorch-${CHANNEL}"::pytorch[build="*${VERSION}*"] \
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"${CUDATOOLKIT}"
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python3 -m pip install torchdata
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python3 setup.py develop
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python3 -m pip install pytest pytest-mock
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# Run Tests
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python3 -m torch.utils.collect_env
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python3 -m pytest \
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--durations=20 \
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--cov=torchvision/prototype/transforms \
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--cov-report=term-missing \
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test/test_prototype_transforms*.py

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