fix(test): deserialization of h5 models w/ custom obj doesn't work in…

… TF2.13

It seems that (de)serialization of h5 models in TF 2.13 has been changed:
custom objects, even with "register_keras_serializable", cannot be loaded.
Two solutions are possible:
- use "with_custom_object_scope()" to load a model with custom objects.
- save model in Keras format and not h5.

The second option was chosen because this format is now preferred for saving
models.

tests/test_layers.py

@@ -226,8 +226,8 @@ def train_k_lip_model(
     )
     empirical_lip_const = evaluate_lip_const(model=model, x=x, seed=42)
     # save the model
-    model_checkpoint_path = os.path.join(logdir, "model.h5")
-    model.save(model_checkpoint_path, overwrite=True, save_format="h5")
+    model_checkpoint_path = os.path.join(logdir, "model.keras")
+    model.save(model_checkpoint_path, overwrite=True)
     del model
     K.clear_session()
     model = load_model(model_checkpoint_path)
@@ -1050,7 +1050,7 @@ def test_vanilla_export(self):
 
         # Test saving/loading model
         with tempfile.TemporaryDirectory() as tmpdir:
-            model_path = os.path.join(tmpdir, "model.h5")
+            model_path = os.path.join(tmpdir, "model.keras")
             model.save(model_path)
             tf.keras.models.load_model(model_path)