When Recurrence meets Transformers to keras 3.0 #1984
Conversation
This file contains 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
fchollet
reviewed
Oct 30, 2024
There was a problem hiding this comment.
Thanks for the PR! I'm not seeing any usage of TF in the example, so does it run on JAX and torch?
The patching operation is done using a
keras.layers.Conv2Dinstance instead of a
traditionaltf.image.extract_patchesto allow for vectorization.
Please update this -- no reference to TF needed.
|
@fchollet, thanks for the review.
It now supports all backends.
Done. |
chunduriv
changed the title
fchollet
approved these changes
Nov 5, 2024
| from tensorflow.keras import layers | ||
| from tensorflow.keras import mixed_precision | ||
| from tensorflow.keras.optimizers import AdamW | ||
| os.environ["KERAS_BACKEND"] = "tensorflow" |
There was a problem hiding this comment.
If it supports all backends, please remove the line that sets the backend.
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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 PR changes the When Recurrence meets Transformers to keras 3.0, as requested in keras-team/keras-cv#2211
Please review the attached gist