code: def load_last_checkpoint(self, args: TrainingArguments) -> None:
      info = det.get_cluster_info()
      assert info
  
      latest_checkpoint = info.latest_checkpoint
      if latest_checkpoint is not None:
          if args.overwrite_output_dir is True:
              logger.info(
                  "Skip downloading last checkpoint from Determined due "
                  "to overwrite_output_dir=True."
              )
              return
  
          # To resume DeepSpeed, each node requires ALL sharded model/optimizer states,
          # so we can skip using selector and just download all files.
          self.core_context.checkpoint.download(
              latest_checkpoint, args.output_dir
          )
  
          checkpoint_path = get_last_checkpoint(args.output_dir)
          args.resume_from_checkpoint = checkpoint_path
  
          logger.info(
              f"Latest checkpoint downloaded to {checkpoint_path}."
          )
  
imports: import json
  import logging
  import os
  from typing import Any, Dict, List, Optional, Tuple
  from transformers import TrainerCallback, TrainerControl, TrainerState, TrainingArguments
  from transformers.trainer_utils import get_last_checkpoint
  import determined
label_desc: Use image node_id 6 for calling the DetCallback obj's underlying member method code with example usage: obj.load_last_checkpoint(args) without return types