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CI: Run tests on PRs, refactor nightly test workflow
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‎.github/workflows/test-runner.yml‎

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name: Test Runner
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on:
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workflow_call:
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inputs:
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platform:
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type: string
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required: true
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description: "Platform: linux-x64, linux-aarch64, windows, macos"
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backend:
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type: string
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required: true
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description: "Backend: cpu, cuda"
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torch_version:
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type: string
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required: true
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description: "PyTorch version to install"
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pypi_index:
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type: string
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default: "https://download.pytorch.org/whl/cpu"
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description: "PyPI index URL for torch installation"
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cuda_version:
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type: string
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default: ""
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description: "CUDA version (required for cuda backend)"
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gpu_type:
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type: string
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default: ""
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description: "GPU type for CUDA testing: T4, L40S"
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# cpu_type currently only affects linux x64 CPU testing to select specific CPU architectures
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cpu_type:
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type: string
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default: ""
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description: "CPU architecture for testing: icelake, cascadelake (default: platform default runner)"
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env:
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BNB_SKIP_CMAKE: 1
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jobs:
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setup:
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runs-on: ubuntu-latest
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outputs:
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build_runner: ${{ steps.map.outputs.build_runner }}
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test_runner: ${{ steps.map.outputs.test_runner }}
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build_os: ${{ steps.map.outputs.build_os }}
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arch: ${{ steps.map.outputs.arch }}
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artifact_name: ${{ steps.map.outputs.artifact_name }}
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steps:
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- name: Map configuration to runners
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id: map
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run: |
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# Map platform to concrete runner names, OS identifiers, and architecture
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case "${{ inputs.platform }}" in
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linux-x64)
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BUILD_OS="ubuntu-22.04"
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BUILD_RUNNER="ubuntu-22.04"
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ARCH="x64"
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if [[ "${{ inputs.backend }}" == "cuda" ]]; then
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case "${{ inputs.gpu_type }}" in
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T4)
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TEST_RUNNER="bandb-aws-g4dn-4xlarge-plus-use1-public-80"
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;;
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L40S)
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TEST_RUNNER="bandb-aws-g6e-4xlarge-plus-use1-public-80"
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;;
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*)
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echo "::error::Must specify gpu_type (T4 or L40S) for linux-x64 cuda backend"
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exit 1
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;;
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esac
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else
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# CPU backend
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case "${{ inputs.cpu_type }}" in
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icelake)
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TEST_RUNNER="banb-aws-general-8-plus-use1-public-80"
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;;
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cascadelake)
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TEST_RUNNER="bandb-aws-g4dn-4xlarge-plus-use1-public-80"
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;;
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"")
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# Default: GitHub-provided runner (AMD EPYC 7763)
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TEST_RUNNER="ubuntu-22.04"
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;;
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*)
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echo "::error::Invalid cpu_type: ${{ inputs.cpu_type }}"
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exit 1
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;;
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esac
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fi
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;;
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linux-aarch64)
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BUILD_OS="ubuntu-22.04-arm"
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BUILD_RUNNER="ubuntu-22.04-arm"
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ARCH="aarch64"
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TEST_RUNNER="ubuntu-22.04-arm"
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;;
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macos)
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BUILD_OS="macos-15"
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BUILD_RUNNER="macos-15"
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ARCH="arm64"
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TEST_RUNNER="macos-15"
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;;
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windows)
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BUILD_OS="windows-2025"
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BUILD_RUNNER="windows-2025"
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ARCH="x64"
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if [[ "${{ inputs.backend }}" == "cuda" ]]; then
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TEST_RUNNER="CUDA-Windows-x64"
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else
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TEST_RUNNER="windows-2025"
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fi
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;;
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*)
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echo "::error::Unsupported platform: ${{ inputs.platform }}"
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exit 1
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;;
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esac
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# Create unique artifact name
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ARTIFACT="lib_${{ inputs.backend }}_${BUILD_OS}_${ARCH}"
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if [[ "${{ inputs.backend }}" == "cuda" ]]; then
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ARTIFACT="${ARTIFACT}_${{ inputs.cuda_version }}"
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fi
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# Add run ID to make artifacts unique across workflow runs
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ARTIFACT="${ARTIFACT}_${{ github.run_id }}_${{ github.run_attempt }}"
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echo "build_runner=${BUILD_RUNNER}" >> $GITHUB_OUTPUT
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echo "test_runner=${TEST_RUNNER}" >> $GITHUB_OUTPUT
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echo "build_os=${BUILD_OS}" >> $GITHUB_OUTPUT
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echo "arch=${ARCH}" >> $GITHUB_OUTPUT
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echo "artifact_name=${ARTIFACT}" >> $GITHUB_OUTPUT
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build:
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needs: setup
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runs-on: ${{ needs.setup.outputs.build_runner }}
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env:
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build_os: ${{ needs.setup.outputs.build_os }}
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build_arch: ${{ needs.setup.outputs.arch }}
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steps:
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- uses: actions/checkout@v4
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# Windows + CUDA: Install CUDA Toolkit
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- name: Install CUDA Toolkit
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if: inputs.backend == 'cuda' && inputs.platform == 'windows'
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uses: Jimver/cuda-toolkit@c35baa1a18fd1fc9dcf47c5bd839bf30559c0bc3 # v0.2.24
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with:
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cuda: ${{ inputs.cuda_version }}
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method: "network"
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sub-packages: '["nvcc","cudart","cusparse","cublas","thrust","nvrtc_dev","cublas_dev","cusparse_dev"]'
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use-github-cache: false
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# Windows: Setup MSVC (needed for both CPU and CUDA builds)
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- name: Setup MSVC
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if: inputs.platform == 'windows'
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uses: ilammy/[email protected]
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# Build CPU backend
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- name: Build C++
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if: inputs.backend == 'cpu'
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run: bash .github/scripts/build-cpu.sh
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# Build CUDA backend
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- name: Build C++ / CUDA
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if: inputs.backend == 'cuda'
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run: bash .github/scripts/build-cuda.sh
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env:
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cuda_version: ${{ inputs.cuda_version }}
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cuda_targets: "75;89"
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- name: Upload build artifact
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uses: actions/upload-artifact@v4
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with:
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name: ${{ needs.setup.outputs.artifact_name }}
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path: output/${{ needs.setup.outputs.build_os }}/${{ needs.setup.outputs.arch }}/*
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retention-days: 7
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test:
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needs: [setup, build]
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runs-on: ${{ needs.setup.outputs.test_runner }}
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env:
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BNB_TEST_DEVICE: ${{ inputs.backend }}
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steps:
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# CUDA: Show GPU information
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- name: Show GPU Information
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if: inputs.backend == 'cuda'
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run: nvidia-smi
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- uses: actions/checkout@v4
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- name: Download build artifact
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uses: actions/download-artifact@v4
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with:
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name: ${{ needs.setup.outputs.artifact_name }}
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path: bitsandbytes/
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merge-multiple: true
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- name: Setup Python
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uses: actions/setup-python@v5
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with:
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python-version: '3.10'
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# Windows: Setup MSVC for torch.compile
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- name: Setup MSVC
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if: inputs.platform == 'windows'
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uses: ilammy/[email protected]
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- name: Install dependencies
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run: |
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pip install torch==${{ inputs.torch_version }} --index-url ${{ inputs.pypi_index }}
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pip install -e ".[test]" -v
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pip install pytest-cov
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# Windows: Downgrade NumPy for torch<2.4.1 compatibility
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# See: https://github.com/pytorch/pytorch/issues/131668
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- name: Downgrade NumPy
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if: inputs.platform == 'windows' && startsWith(inputs.torch_version, '2.3.')
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run: pip install "numpy<2"
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- name: Show installed packages
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run: pip list
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- name: Show environment information
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run: python -m torch.utils.collect_env
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- name: Run tests
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run: pytest --durations=100

‎.github/workflows/tests-nightly.yml‎

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name: Nightly Tests
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on:
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workflow_dispatch:
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schedule:
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# Every day at 02:15 AM UTC
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- cron: "15 2 * * *"
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concurrency:
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group: ${{ github.workflow }}-${{ github.ref }}
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cancel-in-progress: true
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jobs:
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test-cpu:
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name: CPU
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if: github.repository == 'bitsandbytes-foundation/bitsandbytes'
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strategy:
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fail-fast: false
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matrix:
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platform: [linux-x64, linux-aarch64, macos, windows]
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# default runners don't have AVX-512 support, but icelake does
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cpu_type: ["", icelake]
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torch_version: ["2.3.1", "2.8.0", "2.9.1"]
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exclude:
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# aarch64 minimum torch version is 2.5.1
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- platform: linux-aarch64
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torch_version: "2.3.1"
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# icelake only applies to linux-x64
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- platform: linux-aarch64
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cpu_type: icelake
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- platform: macos
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cpu_type: icelake
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- platform: windows
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cpu_type: icelake
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include:
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# Add aarch64 with torch 2.5.1
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- platform: linux-aarch64
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cpu_type: ""
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torch_version: "2.5.1"
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uses: ./.github/workflows/test-runner.yml
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with:
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platform: ${{ matrix.platform }}
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backend: cpu
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torch_version: ${{ matrix.torch_version }}
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pypi_index: "https://download.pytorch.org/whl/cpu"
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cpu_type: ${{ matrix.cpu_type }}
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test-cuda:
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name: CUDA
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if: github.repository == 'bitsandbytes-foundation/bitsandbytes'
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strategy:
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fail-fast: false
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matrix:
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# Linux x64 cross-product
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platform: [linux-x64]
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gpu_type: [T4, L40S]
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cuda_version: ["11.8.0", "12.6.3", "12.8.1", "13.0.1"]
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include:
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# Map CUDA version to torch version and PyPI index
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- cuda_version: "11.8.0"
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torch_version: "2.3.1"
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pypi_index: "https://download.pytorch.org/whl/cu118"
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- cuda_version: "12.6.3"
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torch_version: "2.7.1"
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pypi_index: "https://download.pytorch.org/whl/cu126"
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- cuda_version: "12.8.1"
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torch_version: "2.8.0"
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pypi_index: "https://download.pytorch.org/whl/cu128"
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- cuda_version: "13.0.1"
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torch_version: "2.9.1"
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pypi_index: "https://download.pytorch.org/whl/cu130"
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# Windows CUDA Tests - T4 GPU (CUDA 11.8 only, multiple torch versions)
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- platform: windows
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gpu_type: T4
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cuda_version: "11.8.0"
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torch_version: "2.3.1"
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pypi_index: "https://download.pytorch.org/whl/cu118"
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- platform: windows
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gpu_type: T4
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cuda_version: "11.8.0"
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torch_version: "2.6.0"
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pypi_index: "https://download.pytorch.org/whl/cu118"
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- platform: windows
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gpu_type: T4
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cuda_version: "11.8.0"
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torch_version: "2.7.1" # Note: this is the last PyTorch release supporting CUDA 11.8.
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pypi_index: "https://download.pytorch.org/whl/cu118"
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uses: ./.github/workflows/test-runner.yml
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with:
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platform: ${{ matrix.platform }}
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backend: cuda
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cuda_version: ${{ matrix.cuda_version }}
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gpu_type: ${{ matrix.gpu_type }}
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torch_version: ${{ matrix.torch_version }}
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pypi_index: ${{ matrix.pypi_index }}

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