code: def _wait_for_metrics(self, control: TrainerControl) -> None:
      # Notify Trainer (via TrainerControl) to:
      # (1) log current training metrics,
      # (2) evaluate the model and log evaluation metrics,
      # (3) save the checkpoint.
      #  updating_searcher is as an internal flag that indicates we are
      #  in the process of updating the searcher with the current metrics.
      control.should_log = True
      control.should_evaluate = True
      control.should_save = True
      self.updating_searcher = True
  
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 11 for calling the DetCallback obj's underlying member method code with example usage: obj._wait_for_metrics(control) without return types