When Recurrence meets Transformers to keras 3.0 #1984
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fchollet
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Oct 30, 2024
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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.
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@fchollet, thanks for the review.
It now supports all backends.
Done. |
chunduriv
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fchollet
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Nov 5, 2024
fchollet
reviewed
Nov 15, 2024
| @@ -925,6 +981,12 @@ index = random.randint(0, config["batch_size"]) | |||
| orig_image = images[index] | |||
| overlay_image = upsampled_heat_map[index, ..., 0] | |||
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| if keras.backend.backend() == "torch": | |||
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Please note, if you use ops.convert_to_numpy() you don't need any torch specific code. This is not a blocker so we can merge regardless.
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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