[Python][ML] Add JAX output format to RDataLoader#22550
Open
siliataider wants to merge 3 commits into
Open
Conversation
Test Results 22 files 22 suites 3d 14h 26m 54s ⏱️ For more details on these failures, see this check. Results for commit 781a644. ♻️ This comment has been updated with latest results. |
vepadulano
approved these changes
Jun 10, 2026
vepadulano
left a comment
vepadulano
left a comment
Member
There was a problem hiding this comment.
Thank you for this prompt action following some user feedback! The changes LGTM, I left a couple of minor suggestions. Let's wait for the CI to be ready before merging anyway.
Contributor
Author
|
Thanks! Yes, needs #22551 |
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
This Pull request:
Add
as_jax()as an extra output format toRDataLoaderbatches to support users with JAX-based training pipelines.Batches are retuned as
jax.Arrayobjects.Also has an optional
deviceparameter (mirroring thePyTorchimplementation #22013).Needs #22551 for the tests