  
          Saves the serialized model, with weights, to the folder location specified when
          initializing the plugin. If loss has dropped on both sides of the model, then
          a backup is taken.
          """
          self._io.save(is_exit=is_exit)
  
      def snapshot(self) -> None:
 
</s> remove         self._io.save()  # pylint:disable=protected-access
 </s> add         self._io.save(is_exit=is_exit) </s> remove     def save(self) -> None:
 </s> add     def save(self, is_exit: bool = False) -> None: </s> remove     def __call__(self, y_true: tf.Tensor, y_pred: tf.Tensor) -> tf.Tensor:
 </s> add     def call(self, y_true: tf.Tensor, y_pred: tf.Tensor) -> tf.Tensor:
        Parameters
        ----------
        is_exit: bool, optional
            ``True`` if the save request has come from an exit process request otherwise ``False``
            Default: ``False``
  
          Saves the serialized model, with weights, to the folder location specified when
          initializing the plugin. If loss has dropped on both sides of the model, then
          a backup is taken.
        Parameters
        ----------
        is_exit: bool, optional
            ``True`` if the save request has come from an exit process request otherwise ``False``
            Default: ``False``
          """
          self._io.save(is_exit=is_exit)
  
      def snapshot(self) -> None:
keep keep keep add keep keep keep keep
 Training: Add setting option to save optimizer weights 
plugins/train/model/_base/model.py