CI/CD

Table of Contents

• CI/CD
  • Table of Contents
  • Overview
  • Workflows
    • Code Style Check
    • Unit Test
    • Example Test
      • Example Test on Dispatch
    • Compatibility Test
      • Compatibility Test on Dispatch
    • Release
    • User Friendliness
    • Community
  • Configuration
  • Progress Log

Overview

Automation makes our development more efficient as the machine automatically run the pre-defined tasks for the contributors. This saves a lot of manual work and allow the developer to fully focus on the features and bug fixes. In Colossal-AI, we use GitHub Actions to automate a wide range of workflows to ensure the robustness of the software. In the section below, we will dive into the details of different workflows available.

Workflows

Refer to this documentation on how to manually trigger a workflow. I will provide the details of each workflow below.

A PR which changes the version.txt is considered as a release PR in the following context.

Code Style Check

Workflow Name	File name	Description
post-commit	post_commit.yml	This workflow runs pre-commit checks for changed files to achieve code style consistency after a PR is merged.

Unit Test

Workflow Name	File name	Description
Build on PR	build_on_pr.yml	This workflow is triggered when a PR changes essential files and a branch is created/deleted. It will run all the unit tests in the repository with 4 GPUs.
Build on Schedule	build_on_schedule.yml	This workflow will run the unit tests everyday with 8 GPUs. The result is sent to Lark.
Report test coverage	report_test_coverage.yml	This PR will put up a comment to report the test coverage results when Build is done.

To reduce the average time of the unit test on PR, Build on PR workflow manages testmon cache.

1. When creating a new branch, it copies cache/main/.testmondata* to cache/<branch>/.
2. When creating a new PR or change the base branch of a PR, it copies cache/<base_ref>/.testmondata* to cache/_pull/<pr_number>/.
3. When running unit tests for each PR, it restores testmon cache from cache/_pull/<pr_number>/. After the test, it stores the cache back to cache/_pull/<pr_number>/.
4. When a PR is closed, if it's merged, it copies cache/_pull/<pr_number>/.testmondata* to cache/<base_ref>/. Otherwise, it just removes cache/_pull/<pr_number>.
5. When a branch is deleted, it removes cache/<ref>.

Example Test

Workflow Name	File name	Description
Test example on PR	example_check_on_pr.yml	The example will be automatically tested if its files are changed in the PR
Test example on Schedule	example_check_on_schedule.yml	This workflow will test all examples every Sunday. The result is sent to Lark.
Example Test on Dispatch	example_check_on_dispatch.yml	Manually test a specified example.

Example Test on Dispatch

This workflow is triggered by manually dispatching the workflow. It has the following input parameters:

• example_directory: the example directory to test. Multiple directories are supported and must be separated by comma. For example, language/gpt, images/vit. Simply input language or simply gpt does not work.

Compatibility Test

Workflow Name	File name	Description
Compatibility Test on PR	compatibility_test_on_pr.yml	Check Colossal-AI's compatibility when version.txt is changed in a PR.
Compatibility Test on Schedule	compatibility_test_on_schedule.yml	This workflow will check the compatibility of Colossal-AI against PyTorch specified in .compatibility every Sunday.
Compatibility Test on Dispatch	compatibility_test_on_dispatch.yml	Test PyTorch Compatibility manually.

Compatibility Test on Dispatch

This workflow is triggered by manually dispatching the workflow. It has the following input parameters:

• torch version:torch version to test against, multiple versions are supported but must be separated by comma. The default is value is all, which will test all available torch versions listed in this repository.
• cuda version: cuda versions to test against, multiple versions are supported but must be separated by comma. The CUDA versions must be present in our DockerHub repository.

It only test the compatibility of the main branch

Release

Workflow Name	File name	Description
Draft GitHub Release Post	draft_github_release_post_after_merge.yml	Compose a GitHub release post draft based on the commit history when a release PR is merged.
Publish to PyPI	release_pypi_after_merge.yml	Build and release the wheel to PyPI when a release PR is merged. The result is sent to Lark.
Publish Nightly Version to PyPI	release_nightly_on_schedule.yml	Build and release the nightly wheel to PyPI as colossalai-nightly every Sunday. The result is sent to Lark.
Publish Docker Image to DockerHub after Merge	release_docker_after_merge.yml	Build and release the Docker image to DockerHub when a release PR is merged. The result is sent to Lark.
Check CUDA Extension Build Before Merge	cuda_ext_check_before_merge.yml	Build CUDA extensions with different CUDA versions when a release PR is created.
Publish to Test-PyPI Before Merge	release_test_pypi_before_merge.yml	Release to test-pypi to simulate user installation when a release PR is created.

User Friendliness

Workflow Name	File name	Description
issue-translate	translate_comment.yml	This workflow is triggered when a new issue comment is created. The comment will be translated into English if not written in English.
Synchronize submodule	submodule.yml	This workflow will check if any git submodule is updated. If so, it will create a PR to update the submodule pointers.
Close inactive issues	close_inactive.yml	This workflow will close issues which are stale for 14 days.

Community

Workflow Name	File name	Description
Generate Community Report and Send to Lark	report_leaderboard_to_lark.yml	Collect contribution and user engagement stats and share with Lark every Friday.

Configuration

This section lists the files used to configure the workflow.

1. .compatibility

This .compatibility file is to tell GitHub Actions which PyTorch and CUDA versions to test against. Each line in the file is in the format ${torch-version}-${cuda-version}, which is a tag for Docker image. Thus, this tag must be present in the docker registry so as to perform the test.

2. .cuda_ext.json

This file controls which CUDA versions will be checked against CUDA extension built. You can add a new entry according to the json schema below to check the AOT build of PyTorch extensions before release.

{
  "build": [
    {
      "torch_command": "",
      "cuda_image": ""
    },
  ]
}

Progress Log

• Code style check
  • post-commit check
• unit testing
  • test on PR
  • report test coverage
  • regular test
• release
  • pypi release
  • test-pypi simulation
  • nightly build
  • docker build
  • draft release post
• example check
  • check on PR
  • regular check
  • manual dispatch
• compatibility check
  • check on PR
  • manual dispatch
  • auto test when release
• community
  • contribution report
  • user engagement report
• helpers
  • comment translation
  • submodule update
  • close inactive issue