Skip to content
This repository has been archived by the owner on Jan 13, 2022. It is now read-only.

Latest commit

 

History

History
60 lines (51 loc) · 2.48 KB

CONTRIBUTING.md

File metadata and controls

60 lines (51 loc) · 2.48 KB
Raw

Contributing to Structurally Constrained Recurrent Neural Networks

We want to make contributing to this project as easy and transparent as possible.

Our Development Process

This project is developed internally at Facebook inside a private repository. Changes are periodically pushed to the open-source branch. Pull requests are integrated manually into our private repository first, and they then get propagated to the public repository with the next push.

Pull Requests

We actively welcome your pull requests.

  1. Fork the repo and create your branch from master.
  2. If you've added code that should be tested, add tests
  3. Make sure your code lints.
  4. If you haven't already, complete the Contributor License Agreement ("CLA").

Contributor License Agreement ("CLA")

In order to accept your pull request, we need you to submit a CLA. You only need to do this once to work on any of Facebook's open source projects.

Complete your CLA here: https://code.facebook.com/cla

Issues

We use GitHub issues to track public bugs. Please ensure your description is clear and has sufficient instructions to be able to reproduce the issue.

Coding Style

C++

  • 2 spaces for indentation rather than tabs
  • 80 character line length
  • Name classes LikeThis, functions and methods likeThis, data members likeThis_.
  • Most naming and formatting recommendations from Google's C++ Coding Style Guide apply (but not the restrictions; exceptions and templates are fine.)
  • Feel free to use boost, folly and fbthrift

Lua

  • Inspired by PEP 8
  • 4 spaces for indentation rather than tabs
  • 80 character line length
  • Name classes LikeThis, functions, methods, and variables like_this, private methods _like_this
  • Use Penlight; specifically pl.class for OOP
  • Do not use global variables (except with a very good reason)
  • Use new-style modules; do not use the module() function
  • Assume LuaJIT 2.0+, so Lua 5.1 code with LuaJIT's supported extensions; FFI is okay.

License

By contributing to Structurally Constrained Recurrent Neural Networks, you agree that your contributions will be licensed under its Apache 2.