Why are raw strings preferred for these docstrings?

Raw strings (r""") are used to ensure that LaTeX backslashes used in mathematical formulas are not misinterpreted as Python escape characters.

Can it generate mathematical formulas for tensors?

Yes, it uses Sphinx math directives and LaTeX notation to document the mathematical logic behind tensor operations.

What documentation format does this skill use?

It follows the official PyTorch convention of using raw strings formatted with Sphinx and reStructuredText (reST).

Does it support cross-referencing other PyTorch modules?

Absolutely. It utilizes Sphinx roles like :class:, :func:, and :meth: to create links between related PyTorch components.

How does it handle C-bound functions?

The skill includes specific implementation patterns for the _add_docstr method used in PyTorch's C-bound interfaces.

PyTorch Docstring Expert

Name: PyTorch Docstring Expert
Author: danielzayas

bydanielzayas

Aprendizaje y Documentación

Generates and updates high-quality docstrings for PyTorch functions following strict Sphinx and reStructuredText conventions.

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This skill equips Claude with the specific domain knowledge required to document PyTorch codebases according to official standards. It automates the creation of complex docstrings—including LaTeX mathematical formulas, Sphinx cross-references, and properly formatted argument lists—ensuring documentation consistency across PyTorch-related projects. It is an essential tool for developers contributing to the PyTorch core or building ecosystem libraries that require professional-grade, searchable documentation.

Características Principales

Strict adherence to PyTorch's Sphinx/reST formatting standards
Structured Args and Keyword Args sections with precise type annotations
Intelligent cross-referencing for PyTorch classes, functions, and methods
Support for specialized patterns like C-bound functions and in-place variants
Automatic generation of LaTeX-based mathematical formulas for tensor operations
0 GitHub stars

Casos de Uso

Standardizing documentation for a new PyTorch-based library or extension
Refactoring legacy PyTorch code to meet current official documentation guidelines
Converting mathematical implementation logic into formatted Sphinx docstrings

Acerca de

Características Principales

Strict adherence to PyTorch's Sphinx/reST formatting standards
Structured Args and Keyword Args sections with precise type annotations
Intelligent cross-referencing for PyTorch classes, functions, and methods
Support for specialized patterns like C-bound functions and in-place variants
Automatic generation of LaTeX-based mathematical formulas for tensor operations
0 GitHub stars

Casos de Uso

Standardizing documentation for a new PyTorch-based library or extension
Refactoring legacy PyTorch code to meet current official documentation guidelines
Converting mathematical implementation logic into formatted Sphinx docstrings