  
          logger.info("Loaded model from disk: '%s'", self._filename)
          return model
  
      def save(self) -> None:
          """ Backup and save the model and state file.
  
          Notes
          -----
          The backup function actually backups the model from the previous save iteration rather than
 
</s> remove     def save(self) -> None:
 </s> add     def save(self, is_exit: bool = False) -> None: </s> remove     def _process_gui_triggers(self):
 </s> add     def _process_gui_triggers(self) -> None: </s> remove     def __init__(self, plugin: "ModelBase", model_dir: str, is_predict: bool) -> None:
 </s> add     def __init__(self,
                 plugin: "ModelBase",
                 model_dir: str,
                 is_predict: bool,
                 save_optimizer: Literal["never", "always", "exit"]) -> None:
    def save(self, is_exit: bool = False) -> None:
  
          logger.info("Loaded model from disk: '%s'", self._filename)
          return model
  
    def save(self, is_exit: bool = False) -> None:
          """ Backup and save the model and state file.
  
          Notes
          -----
          The backup function actually backups the model from the previous save iteration rather than
keep keep keep keep replace keep keep keep keep keep
 Training: Add setting option to save optimizer weights 
plugins/train/model/_base/io.py