code: def _pre_load_state_dict_hook(
      state_dict: Union[Dict[str, Tensor], "OrderedDict[str, Tensor]"],
      prefix: str,
      *args: Any,
  ) -> None:
      if not _enable_pre_load_state_dict_hook:
          return
      # Push everything down to ._fpw_module level.
      replace_by_prefix_(state_dict, prefix, prefix + "_fpw_module.")
      # The flat_param_* keys actually needs to move one level up.
      flat_param_key = prefix + "_fpw_module.flat_param"
      for k in list(state_dict.keys()):
          if k.startswith(flat_param_key):
              last_part = k.split(".")[-1]
              assert last_part.startswith("flat_param_"), last_part
              replace_by_prefix_(state_dict, k, prefix + last_part)
  
imports: from contextlib import contextmanager
  from itertools import chain
  import typing
  from typing import TYPE_CHECKING, Any, Dict, Generator, Iterator, List, Mapping, NamedTuple, Optional, Sequence, Set, Tuple, Union, cast
  import torch
  from torch import Tensor
  import torch.nn
  from fairscale.internal.state_dict import replace_by_prefix_
label_desc: Use image node_id 2 for calling a global function with example usage: _pre_load_state_dict_hook(state_dict, prefix) without return types