Loads a keras Model from a SavedModel created by export_saved_model().

This function reinstantiates model state by:

1) loading model topology from json (this will eventually come from metagraph). 2) loading model weights from checkpoint.


import tensorflow as tf

# Create a tf.keras model.
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(1, input_shape=[10]))

# Save the tf.keras model in the SavedModel format.
path = '/tmp/simple_keras_model'
tf.keras.experimental.export_saved_model(model, path)

# Load the saved keras model back.
new_model = tf.keras.experimental.load_from_saved_model(path)

saved_model_path a string specifying the path to an existing SavedModel.
custom_objects Optional dictionary mapping names (strings) to custom classes or functions to be considered during deserialization.

a keras.Model instance.