Remove unused-variable in deeplearning/fbgemm/fbgemm_gpu/codegen/training/backward/embedding_backward_split_cpu_approx_template.cpp +1 #1827
Workflow file for this run
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| # Copyright (c) Meta Platforms, Inc. and affiliates. | |
| # All rights reserved. | |
| # This source code is licensed under the BSD-style license found in the | |
| # LICENSE file in the root directory of this source tree. | |
| # This workflow is used for FBGEMM_GPU-GenAI CI as well as nightly builds of | |
| # FBGEMM_GPU-GenAI against PyTorch-CUDA Nightly. | |
| name: FBGEMM_GPU-GenAI CI | |
| on: | |
| # PR Trigger (enabled for regression checks and debugging) | |
| # | |
| pull_request: | |
| branches: | |
| - main | |
| # Push Trigger (enable to catch errors coming out of multiple merges) | |
| # | |
| push: | |
| branches: | |
| - main | |
| # Cron Trigger (UTC) | |
| # | |
| # Based on the Conda page for PyTorch-nightly, the GPU nightly releases appear | |
| # around 02:30 PST every day (roughly 2 hours after the CPU releases) | |
| # | |
| schedule: | |
| - cron: '45 12 * * *' | |
| # Manual Trigger | |
| # | |
| workflow_dispatch: | |
| inputs: | |
| publish_to_pypi: | |
| description: Publish Artifact to PyPI | |
| type: boolean | |
| required: false | |
| default: false | |
| concurrency: | |
| # Cancel previous runs in the PR if a new commit is pushed | |
| group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} | |
| cancel-in-progress: true | |
| jobs: | |
| # Build on CPU hosts and upload to GHA | |
| build_artifact: | |
| if: ${{ github.repository_owner == 'pytorch' }} | |
| runs-on: ${{ matrix.host-machine.instance }} | |
| container: | |
| image: amazonlinux:2023 | |
| options: --user root | |
| defaults: | |
| run: | |
| shell: bash | |
| env: | |
| PRELUDE: .github/scripts/setup_env.bash | |
| BUILD_ENV: build_binary | |
| BUILD_VARIANT: genai | |
| continue-on-error: true | |
| strategy: | |
| # Don't fast-fail all the other builds if one of the them fails | |
| fail-fast: false | |
| matrix: | |
| host-machine: [ | |
| { arch: x86, instance: "linux.24xlarge" }, | |
| ] | |
| python-version: [ "3.9", "3.10", "3.11", "3.12" ] | |
| cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ] | |
| compiler: [ "gcc", "clang" ] | |
| steps: | |
| - name: Setup Build Container | |
| run: yum update -y; yum install -y binutils findutils git pciutils sudo tar wget which | |
| - name: Checkout the Repository | |
| uses: actions/checkout@v4 | |
| with: | |
| submodules: true | |
| - name: Display System Info | |
| run: . $PRELUDE; print_system_info | |
| - name: Display GPU Info | |
| run: . $PRELUDE; print_gpu_info | |
| - name: Setup Miniconda | |
| run: . $PRELUDE; setup_miniconda $HOME/miniconda | |
| - name: Create Conda Environment | |
| run: . $PRELUDE; create_conda_environment $BUILD_ENV ${{ matrix.python-version }} | |
| - name: Install C/C++ Compilers | |
| run: . $PRELUDE; install_cxx_compiler $BUILD_ENV ${{ matrix.compiler }} | |
| - name: Install Build Tools | |
| run: . $PRELUDE; install_build_tools $BUILD_ENV | |
| - name: Install CUDA | |
| run: . $PRELUDE; install_cuda $BUILD_ENV ${{ matrix.cuda-version }} | |
| # Install via PIP to avoid defaulting to the CPU variant if the GPU variant of the day is not ready | |
| - name: Install PyTorch Nightly | |
| run: . $PRELUDE; install_pytorch_pip $BUILD_ENV nightly cuda/${{ matrix.cuda-version }} | |
| - name: Collect PyTorch Environment Info | |
| if: ${{ success() || failure() }} | |
| run: if . $PRELUDE && which conda; then collect_pytorch_env_info $BUILD_ENV; fi | |
| - name: Install cuDNN | |
| run: . $PRELUDE; install_cudnn $BUILD_ENV "$(pwd)/build_only/cudnn" ${{ matrix.cuda-version }} | |
| - name: Prepare FBGEMM_GPU Build | |
| run: . $PRELUDE; cd fbgemm_gpu; prepare_fbgemm_gpu_build $BUILD_ENV | |
| - name: Build FBGEMM_GPU Wheel | |
| run: . $PRELUDE; cd fbgemm_gpu; build_fbgemm_gpu_package $BUILD_ENV nightly genai | |
| - name: Upload Built Wheel as GHA Artifact | |
| # Cannot upgrade to actions/upload-artifact@v4 yet because GLIBC on the instance is too old | |
| uses: actions/upload-artifact@v3 | |
| with: | |
| name: fbgemm_gpu_nightly_genai_${{ matrix.host-machine.arch }}_${{ matrix.compiler }}_py${{ matrix.python-version }}_cu${{ matrix.cuda-version }}.whl | |
| path: fbgemm_gpu/dist/*.whl | |
| if-no-files-found: error | |
| # Download the built artifact from GHA, test on GPU, and push to PyPI | |
| test_and_publish_artifact: | |
| if: ${{ github.repository_owner == 'pytorch' }} | |
| # Use available instance types - https://github.com/pytorch/test-infra/blob/main/.github/scale-config.yml | |
| runs-on: ${{ matrix.host-machine.instance }} | |
| defaults: | |
| run: | |
| shell: bash | |
| env: | |
| PRELUDE: .github/scripts/setup_env.bash | |
| BUILD_ENV: build_binary | |
| BUILD_VARIANT: genai | |
| ENFORCE_CUDA_DEVICE: 1 | |
| strategy: | |
| fail-fast: false | |
| matrix: | |
| host-machine: [ | |
| { arch: x86, instance: "linux.g5.4xlarge.nvidia.gpu" }, | |
| # TODO: Enable when A100 machine queues are reasonably small enough for doing per-PR CI | |
| # https://hud.pytorch.org/metrics | |
| # { arch: x86, instance: "linux.gcp.a100" }, | |
| ] | |
| python-version: [ "3.9", "3.10", "3.11", "3.12" ] | |
| cuda-version: [ "11.8.0", "12.1.1", "12.4.1" ] | |
| # Specify exactly ONE CUDA version for artifact publish | |
| cuda-version-publish: [ "12.4.1" ] | |
| compiler: [ "gcc", "clang" ] | |
| needs: build_artifact | |
| steps: | |
| # Cannot upgrade to actions/checkout@v4 yet because GLIBC on the instance is too old | |
| - name: Checkout the Repository | |
| uses: actions/checkout@v3 | |
| with: | |
| submodules: true | |
| - name: Download Wheel Artifact from GHA | |
| # Cannot upgrade to actions/download-artifact@v4 yet because GLIBC on the instance is too old | |
| uses: actions/download-artifact@v3 | |
| with: | |
| name: fbgemm_gpu_nightly_genai_${{ matrix.host-machine.arch }}_${{ matrix.compiler }}_py${{ matrix.python-version }}_cu${{ matrix.cuda-version }}.whl | |
| # Use PyTorch test infrastructure action - https://github.com/pytorch/test-infra/blob/main/.github/actions/setup-nvidia/action.yml | |
| - name: Install NVIDIA Drivers and NVIDIA-Docker Runtime | |
| uses: pytorch/test-infra/.github/actions/setup-nvidia@main | |
| - name: Display System Info | |
| run: . $PRELUDE; print_system_info; print_ec2_info | |
| - name: Display GPU Info | |
| run: . $PRELUDE; print_gpu_info | |
| - name: Setup Miniconda | |
| run: . $PRELUDE; setup_miniconda $HOME/miniconda | |
| - name: Create Conda Environment | |
| run: . $PRELUDE; create_conda_environment $BUILD_ENV ${{ matrix.python-version }} | |
| - name: Install C/C++ Compilers for Updated LIBGCC | |
| # Install clang libraries to enable building and install triton | |
| run: . $PRELUDE; install_cxx_compiler $BUILD_ENV clang | |
| - name: Install CUDA | |
| run: . $PRELUDE; install_cuda $BUILD_ENV ${{ matrix.cuda-version }} | |
| # Install via PIP to avoid defaulting to the CPU variant if the GPU variant of the day is not ready | |
| - name: Install PyTorch Nightly | |
| run: . $PRELUDE; install_pytorch_pip $BUILD_ENV nightly cuda/${{ matrix.cuda-version }} | |
| - name: Collect PyTorch Environment Info | |
| if: ${{ success() || failure() }} | |
| run: if . $PRELUDE && which conda; then collect_pytorch_env_info $BUILD_ENV; fi | |
| - name: Prepare FBGEMM_GPU Build | |
| run: . $PRELUDE; cd fbgemm_gpu; prepare_fbgemm_gpu_build $BUILD_ENV | |
| - name: Install FBGEMM_GPU Wheel | |
| run: . $PRELUDE; install_fbgemm_gpu_wheel $BUILD_ENV *.whl | |
| - name: Test with PyTest | |
| timeout-minutes: 30 | |
| run: . $PRELUDE; test_all_fbgemm_gpu_modules $BUILD_ENV | |
| - name: Push Wheel to PyPI | |
| if: ${{ (github.event_name == 'schedule' && matrix.cuda-version == matrix.cuda-version-publish) || (github.event_name == 'workflow_dispatch' && github.event.inputs.publish_to_pypi == 'true' && matrix.cuda-version == matrix.cuda-version-publish) }} | |
| env: | |
| PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }} | |
| run: . $PRELUDE; publish_to_pypi $BUILD_ENV "$PYPI_TOKEN" *.whl |