Skip to content

Latest commit

 

History

History
63 lines (48 loc) · 3.69 KB

CONTRIBUTING.md

File metadata and controls

63 lines (48 loc) · 3.69 KB
Raw

Contribution Guidelines

  1. Create Pull Request
  2. Pull Request Checklist
  3. Pull Request Template
  4. Pull Request Acceptance Criteria
  5. Pull Request Status Checks Overview
  6. Support
  7. Contributor Covenant Code of Conduct

Create Pull Request

If you have improvements to Intel® Neural Compressor, send your pull requests for review. If you are new to GitHub, view the pull request How To.

Step-by-Step guidelines

  • Star this repository using the button Star in the top right corner.
  • Fork this Repository using the button Fork in the top right corner.
  • Clone your forked repository to your pc.
    git clone "url to your repo"
  • Create a new branch for your modifications.
    git checkout -b new-branch
  • Add your files with git add -A, commit git commit -s -m "This is my commit message" and push git push origin new-branch.
  • Create a pull request.

Pull Request Checklist

Before sending your pull requests, follow the information below:

  • Changes are consistent with the Python Coding Style.
  • Add unit tests in Unit Tests to cover the code you would like to contribute.
  • Intel® Neural Compressor has adopted the Developer Certificate of Origin, you must agree to the terms of Developer Certificate of Origin by signing off each of your commits with -s, e.g. git commit -s -m 'This is my commit message'.

Pull Request Template

See PR template

Pull Request Acceptance Criteria

  • At least two approvals from reviewers

  • All detected status checks pass

  • All conversations solved

  • Third-party dependency license compatible

Pull Request Status Checks Overview

Intel® Neural Compressor use Azure DevOps for CI test. And generally use Azure Cloud Instance to deploy pipelines, e.g. Standard E16s v5.

Test Name Test Scope Test Pass Criteria
Code Scan Pylint/Bandit/CopyRight/DocStyle/SpellCheck PASS
DCO Use git commit -s to sign off PASS
Unit Test Pytest scripts under test PASS (No failure, No core dump, No segmentation fault, No coverage drop)
Model Test Pytorch + TensorFlow + ONNX Runtime + MXNet PASS (Functionality pass, FP32/INT8 No performance regression)

Support

Submit your questions, feature requests, and bug reports to the GitHub issues page. You may also reach out to Maintainers.

Contributor Covenant Code of Conduct

This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant Code of Conduct.