from keras import backend as K

K.set_learning_phase(0) # 0 testing, 1 training mode

def h5_to_pb(h5_model, output_dir, model_name, out_prefix="output_", log_tensorboard=True):

    if osp.exists(output_dir) == False:

        os.mkdir(output_dir)

    out_nodes = []

    for i in range(len(h5_model.outputs)):

        out_nodes.append(out_prefix + str(i + 1))

        tf.identity(h5_model.outputs[i], out_prefix + str(i + 1)) //注意此处

    sess = K.get_session()

    from tensorflow.python.framework import graph_util, graph_io

    init_graph = sess.graph.as_graph_def()

    main_graph = graph_util.convert_variables_to_constants(sess, init_graph, out_nodes)

    graph_io.write_graph(main_graph, output_dir, name=model_name, as_text=False)

    if log_tensorboard:

        from tensorflow.python.tools import import_pb_to_tensorboard

        import_pb_to_tensorboard.import_to_tensorboard(osp.join(output_dir, model_name), output_dir)