tf.contrib.saved_model.load_keras_model(saved_model_path)
Defined in tensorflow/contrib/saved_model/python/saved_model/keras_saved_model.py
.
Loads a keras.Model from SavedModel.
load_model reinstantiates model state by: 1) loading model topology from json (this will eventually come from metagraph). 2) loading model weights from checkpoint.
Example:
import tensorflow as tf
# Create a tf.keras model.
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(1, input_shape=[10]))
model.summary()
# Save the tf.keras model in the SavedModel format.
saved_to_path = tf.contrib.saved_model.save_keras_model(
model, '/tmp/my_simple_tf_keras_saved_model')
# Load the saved keras model back.
model_prime = tf.contrib.saved_model.load_keras_model(saved_to_path)
model_prime.summary()
Args:
saved_model_path
: a string specifying the path to an existing SavedModel.
Returns:
a keras.Model instance.