code: def upgrade_state_dict(self, state_dict):
      data_parallel = registry.get("data_parallel") or registry.get(
          "distributed"
      )
      data_parallel = data_parallel or isinstance(
          self.trainer.model,
          (
              torch.nn.DataParallel,
              torch.nn.parallel.DistributedDataParallel,
          ),
      )
      if data_parallel:
          model = self.trainer.model.module
      else:
          model = self.trainer.model
  
      new_dict = {}
      for attr in state_dict:
          new_attr = model.format_state_key(attr)
          if not data_parallel and attr.startswith("module."):
              # In case the ckpt was actually a data parallel model
              # replace first module. from dataparallel with empty string
              new_attr = new_attr.replace("module.", "", 1)
          elif data_parallel and not attr.startswith("module."):
              new_attr = "module." + new_attr
  
          # Log if key has changed but not when the difference
          # is only due to data parallel's `module`
          if new_attr != attr and ("module." + new_attr != attr):
              logger.info(f"Will load key {new_attr} from {attr}")
          new_dict[new_attr] = state_dict[attr]
      return new_dict
  
imports: import glob
  import importlib
  import logging
  import os
  import sys
  import warnings
  from typing import Any, Dict
  import torch
  from mmf.common.registry import registry
  from mmf.utils.checkpoint_updater import get_pretrained_state_mapping_checkpoint
  from mmf.utils.configuration import get_mmf_env, load_yaml
  from mmf.utils.distributed import is_main, is_xla, open_if_main, synchronize
  from mmf.utils.download import download_pretrained_model
  from mmf.utils.file_io import PathManager
  from mmf.utils.general import get_current_device, updir
  from mmf.utils.xla import save_xla_ckpt
  from omegaconf import OmegaConf
label_desc: Use image node_id 10 for calling the Checkpoint obj's underlying member method code with example usage: obj.upgrade_state_dict(state_dict) and returns: new_dict