def load(self, data_path, session, ignore_missing=False):
        data_dict = np.load(data_path,encoding='latin1').item() # read npy
        for key in data_dict:
            with tf.variable_scope(key, reuse=True):
                for subkey in data_dict[key]:
                    try:
                        var = tf.get_variable(subkey)
                        session.run(var.assign(data_dict[key][subkey]))
                        print("assign pretrain model "+subkey+ " to "+key)
                    except ValueError:
                        print("ignore "+key)
                        if not ignore_missing:
                            raise