Improve ssd-training benchmark #3642
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-CPU CI as well as nightly builds of | |
# FBGEMM_GPU-CPU against PyTorch-CPU Nightly. | |
name: FBGEMM_GPU-CPU 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 CPU nightly releases appear | |
# around 00:30 PST every day | |
# | |
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 | |
# https://stackoverflow.com/questions/66335225/how-to-cancel-previous-runs-in-the-pr-when-you-push-new-commitsupdate-the-curre | |
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }} | |
cancel-in-progress: true | |
jobs: | |
# Build on CPU hosts, run tests, and upload to GHA | |
build_artifact: | |
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: cpu | |
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.4xlarge" }, | |
{ arch: arm, instance: "linux.arm64.2xlarge" }, | |
] | |
python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ] | |
compiler: [ "gcc", "clang" ] | |
steps: | |
- name: Setup Build Container | |
run: yum update -y; yum install -y binutils findutils git pciutils sudo wget which | |
- name: Checkout the Repository | |
uses: actions/checkout@v4 | |
- 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 PyTorch-CPU Nightly | |
run: . $PRELUDE; install_pytorch_pip $BUILD_ENV nightly cpu | |
- 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: Build FBGEMM_GPU Wheel | |
run: . $PRELUDE; cd fbgemm_gpu; build_fbgemm_gpu_package $BUILD_ENV nightly cpu | |
- name: Upload Built Wheel as GHA Artifact | |
uses: actions/upload-artifact@v4 | |
with: | |
name: fbgemm_gpu_nightly_cpu_${{ matrix.host-machine.arch }}_${{ matrix.compiler }}_py${{ matrix.python-version }}.whl | |
path: fbgemm_gpu/dist/fbgemm_gpu_nightly_cpu-*.whl | |
# Download the built artifact from GHA, test on GPU, and push to PyPI | |
test_and_publish_artifact: | |
runs-on: ${{ matrix.host-machine.instance }} | |
container: | |
image: amazonlinux:2023 | |
options: --user root | |
defaults: | |
run: | |
shell: bash | |
env: | |
PRELUDE: .github/scripts/setup_env.bash | |
BUILD_ENV: build_binary | |
BUILD_VARIANT: cpu | |
strategy: | |
fail-fast: false | |
matrix: | |
host-machine: [ | |
{ arch: x86, instance: "linux.4xlarge", timeout: 20 }, | |
{ arch: arm, instance: "linux.arm64.2xlarge", timeout: 30 }, | |
] | |
python-version: [ "3.8", "3.9", "3.10", "3.11", "3.12" ] | |
compiler: [ "gcc", "clang" ] | |
needs: build_artifact | |
steps: | |
- name: Setup Build Container | |
run: yum update -y; yum install -y binutils findutils git pciutils sudo wget which | |
- name: Checkout the Repository | |
uses: actions/checkout@v4 | |
- name: Download Wheel Artifact from GHA | |
uses: actions/download-artifact@v4 | |
with: | |
name: fbgemm_gpu_nightly_cpu_${{ matrix.host-machine.arch }}_${{ matrix.compiler }}_py${{ matrix.python-version }}.whl | |
- 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 | |
run: . $PRELUDE; install_cxx_compiler $BUILD_ENV ${{ matrix.compiler }} | |
- name: Install PyTorch-CPU Nightly | |
run: . $PRELUDE; install_pytorch_pip $BUILD_ENV nightly cpu | |
- 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 | |
pwd; ls -la . | |
install_fbgemm_gpu_wheel $BUILD_ENV *.whl | |
- name: Test with PyTest | |
timeout-minutes: ${{ matrix.host-machine.timeout }} | |
run: . $PRELUDE; test_all_fbgemm_gpu_modules $BUILD_ENV | |
- name: Push Wheel to PyPI | |
if: ${{ (github.event_name == 'schedule' || (github.event_name == 'workflow_dispatch' && github.event.inputs.publish_to_pypi == 'true')) && matrix.compiler == 'gcc' }} | |
env: | |
PYPI_TOKEN: ${{ secrets.PYPI_TOKEN }} | |
run: . $PRELUDE; publish_to_pypi $BUILD_ENV fbgemm_gpu_nightly_cpu-*.whl "$PYPI_TOKEN" |