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Optax is a gradient processing and optimization library for JAX. It is designed to facilitate research by providing building blocks that can be recombined in custom ways in order to optimize parametric models such as, but not limited to, deep neural networks. We favor focusing on small composable building blocks that can be effectively combined into custom solutions. Others may build upon these basic components in more complicated abstractions. Whenever reasonable, implementations prioritize readability and structuring code to match standard equations, over code reuse.
Features
- Optax is a gradient processing and optimization library for JAX
- Provides simple, well-tested, efficient implementations of core components
- Documentation available
- Examples available
- Improve research productivity by enabling to easily combine low-level ingredients into custom optimisers (or other gradient processing components)
- Accelerate adoption of new ideas by making it easy for anyone to contribute
- You can install the latest released version of Optax from PyPI
Project Samples
Categories
Machine LearningLicense
Apache License V2.0Follow Optax
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