This tutorial by Felix Köhler provides a step-by-step guide for setting up a DeepONet architecture with JAX and Equinox frameworks for deep learning. The DeepONet is used to evaluate a nonlinear operator on discrete inputs.
“As many as 70 current and former #NewYorkCity public housing employees were charged Tuesday with accepting kickbacks from contractors in exchange for awarding city contracts, federal prosecutors in New York said.
The charges against the New York City Housing Authority employees present the largest number of federal bribery charges brought on a single day in the history of the Department of Justice.”
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@gabmus
I use #rocm 5.7 to run #opencl, google's #jax (for pymc), and #pytorch on two vega cards (Vega 64 and Radeon pro WX9100) on arch and ubuntu. They all run Ok, but correct setup needs some googling around, and jax beeds exporting some #xla flags. Situation is much, much better than 2 years ago, though. @oblomov
Take a listen..
"I don't need no prince to save me
I'm a goddamn CEO
Don't call me "Baby", equal pay me
Snow White said you tried to kiss her
So I'll just buy a new glass slipper and
Burn your castle down
And kids, that's how Cinderella snapped" #JAX#CinderellaSnapped
GPU-based ODE solvers which are 20x-100x faster than those in #jax and #pytorch (programming.dev)
cross-posted from: programming.dev/post/8391233...