          Should only be called from  :class:`lib.cli.launcher.ScriptExecutor`
          """
          logger.debug("Starting Training Process")
          logger.info("Training data directory: %s", self._args.model_dir)
          thread = self._start_thread()
          # from lib.queue_manager import queue_manager; queue_manager.debug_monitor(1)
          err = self._monitor(thread)
 
</s> remove         self.trainer_name = self._args.trainer
 </s> add  </s> remove         self._model.summary(print_fn=lambda x: logger.verbose("%s", x))
 </s> add         if hasattr(self._args, "summary") and self._args.summary:
            print_fn = None  # Print straight to stdout
        else:
            print_fn = lambda x: logger.verbose("%s", x)  # print to logger
        self._model.summary(print_fn=print_fn) </s> remove             if not self._is_predict:
 </s> add             if not is_summary and not self._is_predict:
        if self._args.summary:
            self._load_model()
            return
          Should only be called from  :class:`lib.cli.launcher.ScriptExecutor`
          """
        if self._args.summary:
            self._load_model()
            return
          logger.debug("Starting Training Process")
          logger.info("Training data directory: %s", self._args.model_dir)
          thread = self._start_thread()
          # from lib.queue_manager import queue_manager; queue_manager.debug_monitor(1)
          err = self._monitor(thread)
keep add keep keep keep keep keep
 train - Add option to output model summary and exit 
scripts/train.py