Add tf_keras imports to prepare for Keras 3 (#28588)

* Port core files + ESM (because ESM code is odd)

* Search-replace in modelling code

* Fix up transfo_xl as well

* Fix other core files + tests (still need to add correct import to tests)

* Fix cookiecutter

* make fixup, fix imports in some more core files

* Auto-add imports to tests

* Cleanup, add imports to sagemaker tests

* Use correct exception for importing tf_keras

* Fixes in modeling_tf_utils

* make fixup

* Correct version parsing code

* Ensure the pipeline tests correctly revert to float32 after each test

* Ensure the pipeline tests correctly revert to float32 after each test

* More tf.keras -> keras

* Add dtype cast

* Better imports of tf_keras

* Add a cast for tf.assign, just in case

* Fix callback imports

tests/models/cvt/test_modeling_tf_cvt.py

@@ -22,6 +22,7 @@ if is_tf_available():
     import tensorflow as tf
 
     from transformers import TFCvtForImageClassification, TFCvtModel
+    from transformers.modeling_tf_utils import keras
     from transformers.models.cvt.modeling_tf_cvt import TF_CVT_PRETRAINED_MODEL_ARCHIVE_LIST
 
 
@@ -191,10 +192,10 @@ class TFCvtModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestCase)
 
     @unittest.skip(reason="Get `Failed to determine best cudnn convolution algo.` error after using TF 2.12+cuda 11.8")
     def test_keras_fit_mixed_precision(self):
-        policy = tf.keras.mixed_precision.Policy("mixed_float16")
-        tf.keras.mixed_precision.set_global_policy(policy)
+        policy = keras.mixed_precision.Policy("mixed_float16")
+        keras.mixed_precision.set_global_policy(policy)
         super().test_keras_fit()
-        tf.keras.mixed_precision.set_global_policy("float32")
+        keras.mixed_precision.set_global_policy("float32")
 
     def test_forward_signature(self):
         config, _ = self.model_tester.prepare_config_and_inputs_for_common()