def METHOD_NAME(self, path: str, map_location=None):
    tag = _get_tag_from_path(path)
    first_load_flag = self.tag_flag is None or self.tag_flag == tag
    if not self.enable_nebula_load and first_load_flag:
        self.tag_flag = tag
        logger.info(f"[Nebula] Disable nebula load. Loading checkpoint from {path} ...")
        partition = torch.METHOD_NAME(path, map_location=map_location)
        logger.info(f"[Nebula] Disable nebula load. Loaded checkpoint from {path} .")
        return partition
    partition_name = os.path.basename(path)
    logger.info(f"[Nebula] Loading {path} under tag {tag} from nebula path {self.nebula_load_path}...")
    checkpoint = None
    if tag in (None, 'latest', 'latest_universal'):
        # In some cases, there is the inconsistent tag between deepspeed metadata (latest file)
        # and nebula metadata, will lead to the failure on loading with deepspeed tag. Then we
        # will try to load the valid latest checkpoint from nebula(tier3 > tier1). So, in summary
        # when met failure loading for given tag, the loading priority would be like:
        #               nebula tier3 latest > nebula tier1 latest.
        checkpoint = torch_nebula.get_latest_checkpoint(persist_path=self.nebula_load_path)
    else:
        checkpoint = torch_nebula.get_checkpoint(tag=tag, persist_path=self.nebula_load_path)
    if checkpoint is None or (checkpoint is not None and checkpoint.tag == ''):
        logger.info(
            f"Unable to find valid checkpoint tag:{tag} from Nebula, try to get latest checkpoint again from nebula {self.nebula_load_path} path!"
        )
        # nebula tier3 latest
        checkpoint = torch_nebula.get_latest_checkpoint(persist_path=self.nebula_load_path)
        if checkpoint is None or (checkpoint is not None and checkpoint.tag == ''):
            logger.info(
                f"Unable to find latest checkpoint from Nebula tier3, try to get latest checkpoint again from nebula tier1 path!"
            )
            # nebula tier1 latest
            checkpoint = torch_nebula.get_latest_checkpoint()
            logger.warning(f"Unable to find valid checkpoint from Nebula under tag:{tag}.")
            return None
    tag = checkpoint.tag
    self.tag_flag = -1
    partition = checkpoint.METHOD_NAME(partition_name, map_location=map_location)
    logger.info(f"[Nebula] Loaded {path} under tag {tag} from {self.nebula_load_path}.")
    return partition