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CONTRIBUTING.md

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Thank you for your interest in contributing to ExecuTorch!

This document (CONTRIBUTING.md) covers some of the more technical aspects of contributing.

Coding Style

Goal: Encourage standards that make it easier to read, edit, maintain, and debug the ExecuTorch code.

You can see lintrunner for making sure the code follows our standard. Here's how to set up lintrunner:

pip install lintrunner==0.11.0
pip install lintrunner-adapters==0.11.0
lintrunner init

Python Style

ExecuTorch Python code follows the style used by the PyTorch core project.

C++ Style

ExecuTorch code uses the Google C++ Style, with modifications.

Rationale: Google style is close to the C++ style used by PyTorch core, although PyTorch core does not explicitly document its C++ style. Google style is well documented, and has exceptional tooling support.

Modifications to the Google C++ style, to make it closer to the code in PyTorch core:

  • Function and method names should use lower_snake_case(). This follows the convention that PyTorch core inherited from its namesake Python, and is the biggest modification to the Google C++ style.
  • File names should use lower_snake_case.cpp (not .cc, and not PascalCase.cpp). This follows the most common pattern in PyTorch core.
  • Headers should use #pragma once instead of manual include guards. This follows the most common pattern in PyTorch core.
  • All includes should use <angle brackets>, not "double quotes". This ensures that headers are included using the compiler's include path, and not relative to the local file.
  • Documentation comments should follow Doxygen syntax, either //** ... */ (multi-line) or /// ... (single line), with @-style parameters like @param, @retval. Public APIs must be documented in the .h files that declare them.
  • TODOs should prefer to reference a task or issue number like TODO(#123): <description>, rather than a username. A task can manage much-more-nuanced information, and can change ownership as people leave and join the project.

See the rest of this file for other portability- and efficiency-related modifications to the Google C++ style guide.

C++ Portability Guidelines

See also Portable C++ Programming for detailed advice.

C++ language version

C++11.

NOTE: The code does not yet fully conform to this, and some files require C++17.

Rationale: This is a compromise between being compatible with older, proprietary toolchains, and having access to relatively modern C++ features.

C/C++ standard library usage

Restricted usage of the C++ standard library.

Rationale: ExecuTorch is intended to be portable to bare-metal systems that lack certain features, like dynamic memory, threading, and locking, required by parts of the standard library. It is also intended to be as small as possible, and some convenient stdlib features may grow the binary size unacceptably.

Generally, do not instantiate types that allocate memory under the hood, like std::vector or std::string. Do not call new, malloc() or mmap(); do not use iostreams; do not operate on files.

However, it is convenient and portable (and sometimes necessary) to use static standard library concepts like std::move, or metaprogramming helpers like std::is_floating_point<>. Pure code like <cmath> and <cstring> is fine, as long as you stay away from functions that allocate memory (like strdup()).

It is also allowed (and sometimes necessary) to use "placement new", but be careful to also manually destroy objects initialized in this way.

C++ language features

Exceptions: Do not use.

  • Rationale: Exceptions are not widely supported on some classes of microcontrollers and DSPs, and they can significantly increase binary size.

Threads, thread_local, locking: Do not use, except in optional libraries that must work with threading

  • Rationale: The core runtime must work on systems that do not have threading support.

RTTI, dynamic_cast, and <typeid>: Do not use.

  • Rationale: RTTI adds extra data to every virtual class. ExecuTorch doesn't have a strong need for dynamic_cast and friends, so it's better to reduce the binary size.

Templates and template metaprogramming: Be careful and avoid if possible.

  • Rationale: Most templating results in code generation, and is one of the most common sources of binary bloat. Some use of templates is fine (e.g. an ArrayRef<T>, or code that handles multiple ScalarType types), but for the most part avoid them if possible.

For Backend Delegate Authors

  • Use this guide when integrating your delegate with ExecuTorch.
  • Refer to this set of guidelines when including a third-party depenency for your delegate.