6/11/2023 0 Comments Supermodel init netboard![]() Once again it contains the most popular modules, activation functions, losses, optimizers as well a handful of pre-trained models. Objax: Objax is a third ml library that focuses on object-oriented programming and code readability. ![]() It’s most likely the closest we have in an all-in JAX framework. Jraph: Jraph is a Graph Neural Networks library in JAX.įlax: Flax is another neural network library with a variety of ready-to-use modules, optimizers, and utilities. RLax: RLax is a reinforcement learning framework with many RL subcomponents and operations.Ĭhex: Chex is a library of utilities for testing and debugging JAX code. Optax: Optax is a gradient processing and optimization library that contains out-of-the-box optimizers and related mathematical operations. It provides some simple, composable abstractions for machine learning research as well as ready-to-use modules and layers. Haiku: Haiku is the go-to framework for Deep Learning and it’s used by many Google and Deepmind internal teams. The people in Deepmind seem to be very busy and have already released a plethora of frameworks on top of JAX. One of the common problems people have when starting with JAX is the choice of a framework. Also you can find the full code in our Github repository. ![]() Despite the fact that it lacks the maturity of Tensorflow or Pytorch, it provides some great features for building and training Deep Learning models.įor a solid understanding of JAX basics, check my previous article if you haven’t already. As JAX is growing in popularity, more and more developer teams are starting to experiment with it and incorporating it into their projects. And what better model to choose than the Transformer. In this tutorial, we will explore how to develop a Neural Network (NN) with JAX.
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