hi,

I am having trouble loading large model after saving.

have tried all below saveing methods:

```
tf.saved_model.save(model, model_save_path)
model.save(model_save_path+"_new_save")
tf.keras.models.save_model(model, model_save_path+"_v3")
```

error when loading :

method 1

```
m2=tf.keras.models.load_model(model_save_path+"_v3")
error:
__init__() got an unexpected keyword argument 'reduction'
```

method 2

```
m3=tf.keras.models.load_model(model_save_path
error:
ARNING:tensorflow:SavedModel saved prior to TF 2.5 detected when loading Keras model. Please ensure that you are saving the model with model.save() or tf.keras.models.save_model(), *NOT* tf.saved_model.save(). To confirm, there should be a file named "keras_metadata.pb" in the SavedModel directory.
ValueError: Unable to create a Keras model from SavedModel at xxxx . This SavedModel was exported with `tf.saved_model.save`, and lacks the Keras metadata file. Please save your Keras model by calling `model.save`or `tf.keras.models.save_model`. Note that you can still load this SavedModel with `tf.saved_model.load`.
```

method 3

```
m4=tf.saved_model.load(model_save_path)
this works but m4 object has no predict method
and not able to use
model.signatures["serving_default"](**input_data)
or
model.__call__(input_data,training=False)
to predict on data
```

any help would be appreciated