Re:PyTorch vs. TensorFlow in 2022
by mrdoops on Tuesday December 14, 2021 @12:51PM
(#29554720)
Yep and this approach also allows languages like Julia and Elixir to compile their expressions into valid compute graphs that target JAX/XLA. That polyglot capability opens up cutting edge machine learning into quite a bit more ecosystems with another level of capabilities in distribution and fault tolerance as is the case with Elixir + Nx.
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Could you or someone elaborate more on how other languages can hook into JAX/XLA?
Julia has XLA.jl [0] which interoperate with their deep-learning stack and Elixir has NX [1] which is higher level (basically JAX but in Elixir). I would love to see someone do something like that in Rust...