code: def _write_training_progress(
      train_progress: Progress, loggers: List[MetricLogger]
  ) -> None:
      if not loggers:
          return
  
      step = train_progress.num_steps_completed
      epoch = train_progress.num_epochs_completed
      for logger in loggers:
          logger.log("Training steps completed vs epochs", step, epoch)
  
file_path: tnt/torchtnt/framework/callbacks/train_progress_monitor.py
imports: from typing import List, Union
  from torchtnt.framework.callback import Callback
  from torchtnt.framework.state import State
  from torchtnt.framework.unit import TTrainUnit
  from torchtnt.utils.loggers.logger import MetricLogger
  from torchtnt.utils.progress import Progress
label_desc: Use image node_id 1 for calling a global function with example usage: _write_training_progress(train_progress, loggers) without return types