Преобразование модели Keras .h5 в модель Tensorflow .pb

питон

import tensorflow as tf
from keras import backend as K
# This line must be executed before loading Keras model.
K.set_learning_phase(0)
from tensorflow.python.framework.graph_util import convert_variables_to_constants
from keras.models import load_model
model = tf.keras.models.load_model(‘./keras_model.h5’)
def freeze_session(session, keep_var_names=None, output_names=None,clear_devices=True):
 graph = session.graph
 with graph.as_default():
 freeze_var_names = list(set(v.op.name for v in tf.global_variables()).difference(keep_var_names or []))
 output_names = output_names or []
 output_names += [v.op.name for v in tf.global_variables()]
 # Graph -> GraphDef ProtoBuf
 input_graph_def = graph.as_graph_def()
 if clear_devices:
 for node in input_graph_def.node:
 node.device = “”
 frozen_graph = convert_variables_to_constants(session, input_graph_def, output_names, freeze_var_names)
 return frozen_graph
frozen_graph = freeze_session(K.get_session(), output_names=[out.op.name for out in model.outputs])
tf.train.write_graph(frozen_graph, “model”, “tf_model.pb”, as_text=False)