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python39-jax - Differentiate, compile, and transform Numpy code
- Description:
JAX is Autograd and XLA, brought together for high-performance
numerical computing, including large-scale machine learning research.
With its updated version of Autograd, JAX can automatically
differentiate native Python and NumPy functions. It can differentiate
through loops, branches, recursion, and closures, and it can take
derivatives of derivatives of derivatives. It supports reverse-mode
differentiation (a.k.a. backpropagation) via grad as well as
forward-mode differentiation, and the two can be composed arbitrarily
to any order.
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