tjax 0.22.4

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 and mypy_plugin decorator dataclasss that facilitates defining structured JAX objects (so-called “pytrees”), which benefits from:

  • the ability to mark fields as static (not available in chex.dataclass),

  • a MyPy plugin, and

  • a display method that produces formatted text according to the tree structure.

• A fixed_point finding library heavily based on fax. Our library

  • supports stochastic iterated functions, and

  • uses dataclasses instead of closures to avoid leaking JAX tracers.

• 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.

Minor components

Tjax also includes:

• A pretty printer print_generic for aggregate and vector types, including dataclasses. (See display.)

• Versions of custom_vjp and custom_jvp that support being used on methods. (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 Matplotlib trajectory plotter PlottableTrajectory. (See plottable_trajectory.)

• 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.)

Also, see the documentation.

Contribution guidelines

• Conventions: PEP8.

• How to run tests: pytest .

• How to clean the source:

  • isort .

  • mypy .

  • pylint tjax tests

  • pflake8 .