PIX

Functions are designed to work with JAX transformations like jax.jit, jax.vmap, and jax.pmap, enabling automatic optimization and parallelization directly within JAX workflows, as shown in the quickstart examples.

Leverages JAX's XLA compilation for GPU/TPU support, providing significant speedups for image processing in machine learning pipelines, which is ideal for research requiring heavy computation.

Written in pure Python with straightforward installation via pip, making it accessible despite underlying C++ dependencies through JAX, as noted in the installation instructions.

Built for machine learning research, with examples and testing suites that facilitate experimentation, such as data augmentation for JAX models, aligning with its goal in the DeepMind JAX Ecosystem.