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Anything that can be implemented in JAX *will* be implemented in JAX. Here's a differentiable path tracer (and a tutorial!) Blog Post: https://blog.evjang.com/2019/11/jaxpt.html … Code: https://github.com/ericjang/pt-jax pic.twitter.com/KBHnCqka2e
So say I don’t care about running on TPUs (I know the pains of TF + TPUs all to well) what are some “killer features” of JAX over PyTorch?
Vmap and pmap are the biggest ones that come to mind. I’ve heard anecdotally that JAX can be much faster on some workloads (don’t quote me). I expect pytorch devs to catch up eventually though.
By the way, JAX *just works* on TPU. It’s nothing like TF + TPU 
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