google-deepmind/optax
A composable gradient processing and optimization library for the JAX machine learning framework.
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Optax provides building blocks for creating custom optimizers and gradient processing components within the JAX ecosystem. Originally developed internally at DeepMind as jax.experimental.optix, it offers implementations of popular optimizers and loss functions designed for research productivity. The library emphasizes composability, allowing researchers to combine low-level components into custom solutions.
Frequently asked
- What is google-deepmind/optax?
- A composable gradient processing and optimization library for the JAX machine learning framework.
- Is optax open source?
- Yes — google-deepmind/optax is open source, released under the Apache-2.0 license.
- What language is optax written in?
- google-deepmind/optax is primarily written in Python.
- How popular is optax?
- google-deepmind/optax has 2.3k stars on GitHub.
- Where can I find optax?
- google-deepmind/optax is on GitHub at https://github.com/google-deepmind/optax.