Unifying TBE API using List (Frontend) - reland #76
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-CUDA Benchmarking | |
name: FBGEMM_GPU-CUDA Benchmark | |
on: | |
# PR Trigger (enabled for regression checks and debugging) | |
# | |
pull_request: | |
branches: | |
- main | |
# Manual Trigger | |
# | |
workflow_dispatch: | |
inputs: | |
pytorch_channel_version: | |
description: Package Channel + Version to Use for PyTorch Installation, in `<channel>[/<version>]` Format | |
type: string | |
required: false | |
default: "" | |
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: cuda | |
BUILD_CUDA_VERSION: ${{ matrix.cuda-version }} | |
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: [ "3.13" ] | |
cuda-version: [ "12.8.0" ] | |
compiler: [ "gcc" ] | |
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 ${{ (github.event_name == 'workflow_dispatch' && github.event.inputs.pytorch_channel_version) || 'nightly' }} cuda/${{ 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 $BUILD_ENV nightly cuda | |
- name: Upload Built Wheel as GHA Artifact | |
uses: actions/upload-artifact@v4 | |
with: | |
name: fbgemm_gpu_nightly_cuda_${{ 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 and test on GPU | |
benchmark_artifact: | |
if: ${{ github.repository_owner == 'pytorch' }} | |
# runs-on: linux.4xlarge.nvidia.gpu | |
# 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: cuda | |
BUILD_CUDA_VERSION: ${{ matrix.cuda-version }} | |
ENFORCE_CUDA_DEVICE: 1 | |
strategy: | |
fail-fast: false | |
matrix: | |
host-machine: [ | |
{ arch: x86, instance: "linux.g5.4xlarge.nvidia.gpu" }, | |
# TODO: Enable when A100 machine queues are reasonably small enough for doing per-PR CI | |
# https://hud.pytorch.org/metrics | |
# { arch: x86, instance: "linux.gcp.a100" }, | |
] | |
python-version: [ "3.13" ] | |
cuda-version: [ "12.8.0" ] | |
compiler: [ "gcc" ] | |
needs: build_artifact | |
steps: | |
# Cannot upgrade to actions/checkout@v4 yet because GLIBC on the instance is too old | |
- name: Checkout the Repository | |
uses: actions/checkout@v4 | |
with: | |
submodules: true | |
- name: Download Wheel Artifact from GHA | |
# Cannot upgrade to actions/download-artifact@v4 yet because GLIBC on the instance is too old | |
uses: actions/download-artifact@v4 | |
with: | |
name: fbgemm_gpu_nightly_cuda_${{ 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 Build Tools | |
run: . $PRELUDE; install_build_tools $BUILD_ENV | |
- name: Install C/C++ Compilers for Updated LIBGCC | |
# NOTE: gcc is required for torch dynamo to work properly, as some of | |
# the compilation flags used by torch dynamo are gcc-specific: | |
# | |
# clang-16: error: unknown argument: '-fno-tree-loop-vectorize' | |
run: . $PRELUDE; install_cxx_compiler $BUILD_ENV gcc | |
- 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 ${{ (github.event_name == 'workflow_dispatch' && github.event.inputs.pytorch_channel_version) || 'nightly' }} cuda/${{ 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: Run FBGEMM_GPU Benchmark | |
timeout-minutes: 40 | |
run: . $PRELUDE; run_tbe_microbench $BUILD_ENV |