keras model conversion/save; convert keras format (hdf5) into tensorflow SavedModelBuilder (protobuf)

hdf5_to_pb.py

import tensorflow as tf
from tensorflow.python.saved_model import tag_constants
from tensorflow.python.saved_model.signature_def_utils_impl import predict_signature_def

KERAS_HDF5 = 'weights.hdf5'
EXPORT_PATH = '/tmp/tf_model/'  # where to save the tensorflow model


model = create_model(params)  # build and compile the architecture
model.load_weights(KERAS_HDF5)

# initialize variables, session, graph
sess = tf.keras.backend.get_session()
graph = tf.get_default_graph()

init=tf.global_variables_initializer()
sess.run(init)

with graph.as_default():
    temp_export_path = EXPORT_PATH

    # Saving
    builder = tf.saved_model.builder.SavedModelBuilder(temp_export_path)
    signature = predict_signature_def(inputs={'state': model.input},
                                      outputs={t.name: t for t in model.outputs})
    builder.add_meta_graph_and_variables(sess, [tag_constants.SERVING],
                                         signature_def_map={
                                             tf.saved_model.signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signature})
    builder.save()