llama.cpp/CONTRIBUTING.md

Pull requests (for contributors)

• Test your changes:
  • Using the commands in the tests folder. For instance, running the ./tests/test-backend-ops command tests different backend implementations of the GGML library
  • Execute the full CI locally on your machine before publishing
• Please rate the complexity of your PR (i.e. Review Complexity : Low, Review Complexity : Medium, Review Complexity : High). This makes it easier for maintainers to triage the PRs.
  • The PR template has a series of review complexity checkboxes [ ] that you can mark as [X] for your convenience
• Consider allowing write access to your branch for faster review
• If your PR becomes stale, don't hesitate to ping the maintainers in the comments

Pull requests (for collaborators)

• Squash-merge PRs
• Use the following format for the squashed commit title: <module> : <commit title> (#<issue_number>). For example: utils : fix typo in utils.py (#1234)
• Optionally, pick a <module> from here: https://github.com/ggerganov/llama.cpp/wiki/Modules

Coding guidelines

• Avoid adding third-party dependencies, extra files, extra headers, etc.
• Always consider cross-compatibility with other operating systems and architectures
• Avoid fancy looking modern STL constructs, use basic for loops, avoid templates, keep it simple
• There are no strict rules for the code style, but try to follow the patterns in the code (indentation, spaces, etc.). Vertical alignment makes things more readable and easier to batch edit
• Clean-up any trailing whitespaces, use 4 spaces for indentation, brackets on the same line, void * ptr, int & a
• Naming usually optimizes for common prefix (see https://github.com/ggerganov/ggml/pull/302#discussion_r1243240963)
• Tensors store data in row-major order. We refer to dimension 0 as columns, 1 as rows, 2 as matrices
• Matrix multiplication is unconventional: C = ggml_mul_mat(ctx, A, B) means C^T = A B^T \Leftrightarrow C = B A^T.

Resources

The Github issues, PRs and discussions contain a lot of information that can be useful to get familiar with the codebase. For convenience, some of the more important information is referenced from Github projects:

https://github.com/ggerganov/llama.cpp/projects