Product Information
Overview
JAX is NumPy on the CPU, GPU, and TPU, with great automatic differentiation for high-performance machine learning research.
Core advantages (features)
With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy code. It can differentiate through a large subset of Python’s features, including loops, ifs, recursion, and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode as well as forward-mode differentiation, and the two can be composed arbitrarily to any order.
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