Cant properly load saved model and call predict method

Question

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

Answer 1

Adding compile=False to the load function will solve the issue:

m2=tf.keras.models.load_model(model_save_path+"_v3", compile=False)