GitHub - google/jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
JAX
JAX is a Python library designed for high-performance numerical computing, especially machine learning research. It combines Autograd and XLA for high-performance machine learning research. 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.