jax

This issue is part of our Doc Test Sprint. If you're interested in helping out come join us on Discord and talk with other contributors!

Docstring examples are often the first point of contact when trying out a new library! So far we haven't done a very good job at ensuring that all docstring examples work correctly in 🤗 Transformers - but we're now very

It would be great if you could add the JAX equivalent of scipy.stats.mode, which is currently unavailable.

A use case may be a ML classification task with ensembles, where multiple models give different predictions, and we are interested in finding the most common one.

As an example, consider predictions to be a two-dimensional DeviceArray of predictions, with
shape = (number of model

Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?

Love the book! Ran into this display issue when viewing it on Chrome's PDF viewer:

Dear Numpyro developers,

Please develop Euler Maruyama features in numpyro similar to features found in PyMC.

Thanks alot.

Dear Brax team,

Since Brax is fully differentiable, I thought it'd be possible to use it like DiffTaichi or GradSim for system identification (e.g. determining the mass of an object from a trajectory and known force) but I couldn't find any example for this.
Do you happen to have any demo or tips for this?

From the top of my head I would do something like this:
Let's say the task is to es

jit and unroll don't seem to be documented in https://jaxopt.github.io/stable/_autosummary/jaxopt.GradientDescent.html#jaxopt-gradientdescent