What happened to XLA.jl

[jar1]

Related issues

Julia's Broadcast vs Jax's vmap

My (high-level) understanding of jax.vmap is that it automatically vectorizes vectorizes a function along a specified axis of its input by introducing an “abstract” axis and compiling the code as though the inputs were shaped accordingly. To see the difference let’s consider a very simple example where Julia’s broadcasting is much less performant than jax.vmap. Let’s consider how jax internally represents vector-vector dot products: import jax.numpy as np from jax.api import jit, vmap from j…