code: def load_checkpoint(
      model,
      filename,
      map_location=None,
      strict=False,
      logger=None,
      revise_keys=[(r"^module\.", "")],
  ):
      """Load checkpoint from a file or URI.
  
      Args:
          model (Module): Module to load checkpoint.
          filename (str): Accept local filepath, URL, ``torchvision://xxx``,
              ``open-mmlab://xxx``. Please refer to ``docs/model_zoo.md`` for
              details.
          map_location (str): Same as :func:`torch.load`.
          strict (bool): Whether to allow different params for the model and
              checkpoint.
          logger (:mod:`logging.Logger` or None): The logger for error message.
          revise_keys (list): A list of customized keywords to modify the
              state_dict in checkpoint. Each item is a (pattern, replacement)
              pair of the regular expression operations. Default: strip
              the prefix 'module.' by [(r'^module\\.', '')].
  
      Returns:
          dict or OrderedDict: The loaded checkpoint.
      """
      checkpoint = _load_checkpoint(filename, map_location, logger)
      # OrderedDict is a subclass of dict
      if not isinstance(checkpoint, dict):
          raise RuntimeError(
              f"No state_dict found in checkpoint file {filename}"
          )
      # get state_dict from checkpoint
      if "state_dict" in checkpoint:
          state_dict = checkpoint["state_dict"]
      else:
          state_dict = checkpoint
  
      # strip prefix of state_dict
      metadata = getattr(state_dict, "_metadata", OrderedDict())
      for p, r in revise_keys:
          state_dict = OrderedDict(
              {re.sub(p, r, k): v for k, v in state_dict.items()}
          )
      # Keep metadata in state_dict
      state_dict._metadata = metadata
  
      # load state_dict
      load_state_dict(model, state_dict, strict, logger)
      return checkpoint
  
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 17 for calling a global function with example usage: load_checkpoint(model, filename, map_location, strict, logger, revise_keys) and returns: checkpoint