def METHOD_NAME(checkpoint, config):
    """
    Load checkpoint and re-save it.
    """
    load_checkpoint(checkpoint, config.ckpt_path)
    if config.checkpoint_save_dir is None:
        config.checkpoint_save_dir = config.log_dir
    checkpoint_manager = tf.train.CheckpointManager(checkpoint, config.checkpoint_save_dir, max_to_keep=None)
    save_path = checkpoint_manager.save()
    logger.info("Saved checkpoint: {}".format(save_path))