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Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more - jax/docs/developer.md at main · google/jax

With its updated version of Autograd,\nJAX can automatically differentiate native\nPython and NumPy functions. It can differentiate through loops, branches,\nrecursion, and closures, and it can take …

Building jaxlib from source with a modified XLA repository. JAX depends on XLA, whose source code is in the XLA GitHub repository. By default JAX uses a pinned copy of the XLA repository, but we often …

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Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more - Align the custom_call implementation in mlir and hlo_helpers. · google/jax@24f9011

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.. toctree::\n :maxdepth: 1\n\n jax.numpy\n jax.scipy\n jax.example_libraries\n jax.experimental\n jax.image\n jax.lax\n jax.nn\n jax.ops\n jax.random\n jax.tree_util\n jax.flatten_util\n jax.dlpack\n …

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more - PR #17528 · google/jax@cb28eb3

Dear Jax team, There is an issue (#12402) about problems with Bessel function support in core Jax. In particular, the Bessel Jv functions (and especially J0 and J1) are the basis functions of the H...