PR #17648: SpectralNormalization

Imported from GitHub PR https://github.com/keras-team/keras/pull/17648

Hello,

  here is the adapted `SpectralNormalization` from TF-Addons implementation.

Thanks.
Copybara import of the project:

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0ae1ae70024b548fc2aee47c976ca4c30530157f by Martin Kubovcik <markub3327@gmail.com>:

+ SpectralNormalization

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7f91062eea8d23f6407a2c3bc253e82e48a52e30 by Martin Kubovcik <markub3327@gmail.com>:

fixes

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5fbe19ecadbdf69acb13f1b3aac3c411b1427c83 by Martin Kubovcik <markub3327@gmail.com>:

fix

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f57b45aa5a635a3d75ec957e9ca3f7ce5984421c by Martin Kubovcik <markub3327@gmail.com>:

update

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46269ea5fc5d404051c47a7eadcd42acd2a62ad6 by Martin Kubovcik <markub3327@gmail.com>:

update tests

Merging this change closes #17648

PiperOrigin-RevId: 520171696
This commit is contained in:
Bc. Martin Kubovčík 2023-03-28 16:50:26 -07:00 committed by TensorFlower Gardener
parent 1537ab8907
commit afec73aba0

View File

@ -59,6 +59,8 @@
libraries (like sklearn or pycocotools) into Keras as first-class Keras
metrics.
* Added `tf.keras.optimizers.Lion` optimizer.
* Added `tf.keras.layers.SpectralNormalization` layer wrapper to perform
spectral normalization on the weights of a target layer.
* The `SidecarEvaluatorModelExport` callback has been added to Keras as
`keras.callbacks.SidecarEvaluatorModelExport`. This callback allows for
exporting the model the best-scoring model as evaluated by a