logistic_regression.py 文件源码

def freeze_graph(
        model_dir, output_nodes_list, output_graph_name='frozen_model.pb'
):
    """
    reduce a saved model and metadata down to a deployable file
    """
    from tensorflow.python.framework import graph_util

    LOGGER.info('Attempting to freeze graph at {}'.format(model_dir))
    checkpoint = tf.train.get_checkpoint_state(model_dir)
    input_checkpoint = checkpoint.model_checkpoint_path

    if input_checkpoint is None:
        LOGGER.error('Cannot load checkpoint at {}'.format(model_dir))
        return None

    absolute_model_dir = '/'.join(input_checkpoint.split('/')[:-1])
    output_graph = absolute_model_dir + '/' + output_graph_name
    saver = tf.train.import_meta_graph(input_checkpoint + '.meta',
                                       clear_devices=True)
    graph = tf.get_default_graph()
    input_graph_def = graph.as_graph_def()

    with tf.Session() as sess:
        saver.restore(sess, input_checkpoint)
        output_graph_def = graph_util.convert_variables_to_constants(
            sess, input_graph_def, output_nodes_list
        )
        with tf.gfile.GFile(output_graph, 'wb') as f:
            f.write(output_graph_def.SerializeToString())
        LOGGER.info('Froze graph with {} ops'.format(
            len(output_graph_def.node)
        ))

    return output_graph