Tools for JAX

This repository implements a variety of tools for the differential programming library JAX.

Major components

Tjax's major components are:

• A dataclass decorator dataclass that facilitates defining structured JAX objects (so-called "pytrees"), which benefits from:
  • the ability to mark fields as static (not available in chex.dataclass), and
  • a display method that produces formatted text according to the tree structure.
• A shim for the gradient transformation library optax that supports:
  • easy differentiation and vectorization of “gradient transformation” (learning rule) parameters,
  • gradient transformation objects that can be passed dynamically to jitted functions, and
  • generic type annotations.
• A pretty printer print_generic for aggregate and vector types, including dataclasses. (See display.) It features:
  • support for traced values,
  • colorized tree output for aggregate structures, and
  • formatted tabular output for arrays (or statistics when there's no room for tabular output).

Minor components

Tjax also includes:

• Versions of custom_vjp and custom_jvp that support being used on methods: custom_vjp_method and custom_vjp_method (See shims.)
• Tools for working with cotangents. (See cotangent_tools.)
• JAX tree registration for NetworkX graph types. (See graph.)
• Leaky integration leaky_integrate and Ornstein-Uhlenbeck process iteration diffused_leaky_integrate. (See leaky_integral.)
• An improved version of jax.tree_util.Partial. (See partial.)
• A testing function assert_tree_allclose that automatically produces testing code. And, a related function tree_allclose. (See testing.)
• Basic tools like divide_where. (See tools.)

Contribution guidelines

• Conventions: PEP8.
• How to run tests: pytest .
• How to clean the source:
  • ruff .
  • pyright
  • mypy
  • isort .
  • pylint tjax tests