code: def _load_from_zoo(self, file):
      ckpt_config = self.trainer.config.checkpoint
      zoo_ckpt = load_pretrained_model(file)
  
      # If zoo_config_override, load the model directly using `from_pretrained`
      if ckpt_config.zoo_config_override:
          model_cls = registry.get_model_class(
              self.trainer.config.model
          )
          self.trainer.model = model_cls.from_pretrained(
              ckpt_config.resume_zoo
          )
          self.trainer.config.model_config = zoo_ckpt[
              "full_config"
          ].model_config
          return None, False
      else:
          return self.upgrade_state_dict(zoo_ckpt["checkpoint"]), True
  
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 11 for calling the Checkpoint obj's underlying member method code with example usage: obj._load_from_zoo(file) and returns: None,  False, self,  True