              kwargs["profile_batch"] = 0
          logger.debug(kwargs)
          return kwargs
  
      def __print_loss(self, loss):
          """ Outputs the loss for the current iteration to the console.
  
          Parameters
          ----------
          loss: dict
 
</s> remove             trainer.train_one_step(viewer, timelapse)
 </s> add             trainer.train_one_step(viewer, timelapse, self._args.colab) </s> remove             exit(0)
 </s> add             sys.exit(0) </s> remove         print("[{}] [#{:05d}] {}".format(self._timestamp,
                                         self._model.iterations,
                                         output), end='\r')
 </s> add         output = "[{}] [#{:05d}] {}".format(self._timestamp, self._model.iterations, output)
        if not is_colab:
            print(output, end='\r')
        else:
            print(output)
    def __print_loss(self, loss, is_colab):
              kwargs["profile_batch"] = 0
          logger.debug(kwargs)
          return kwargs
  
    def __print_loss(self, loss, is_colab):
          """ Outputs the loss for the current iteration to the console.
  
          Parameters
          ----------
          loss: dict
keep keep keep keep replace keep keep keep keep keep
 lib,cli: Add suppressed colab flag 
plugins/train/trainer/_base.py