code: def _load_checkpoint(filename, map_location=None, logger=None):
      """Load checkpoint from somewhere (modelzoo, file, url).
  
      Args:
          filename (str): Accept local filepath, URL, ``torchvision://xxx``,
              ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
              details.
          map_location (str, optional): Same as :func:`torch.load`.
             Default: None.
          logger (:mod:`logging.Logger`, optional): The logger for error message.
             Default: None
  
      Returns:
          dict or OrderedDict: The loaded checkpoint. It can be either an
             OrderedDict storing model weights or a dict containing other
             information, which depends on the checkpoint.
      """
      return CheckpointLoader.load_checkpoint(
          filename, map_location, logger
      )
  
imports: import io
  import os
  import os.path
  import pkgutil
  import re
  import time
  import warnings
  from collections import OrderedDict
  from importlib import import_module
  from tempfile import TemporaryDirectory
  import torch
  import torchvision
  from torch.optim import Optimizer
  from torch.utils import model_zoo
  import annotator.uniformer.mmcv
  from ..fileio import FileClient
  from ..fileio import load
  from ..parallel import is_module_wrapper
  from ..utils import mkdir_or_exist
  from .dist_utils import get_dist_info
label_desc: Use image node_id 15 for calling a global function with example usage: _load_checkpoint(filename, map_location, logger) and returns: CheckpointLoader