JuliaPy / JuliaPy/PythonCall.jl
PythonCall With Jax: Fast inference w/ numpy but does not work with jax.grad need jax.numpy, which is slow, for gradient
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描述
I need Jax for something that Zygote cannot do well (meta-learning) and someone recommended PythonCall as a solution to some issues I was having with PyCall.
So far, PythonCall has been great. Things work and it is generally quite quick.
There is one pain point: jax.grad does not work with numpy.array
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