                  continue
              model.summary(line_length=100, print_fn=print_fn)
          parent.summary(line_length=100, print_fn=print_fn)
  
      def save(self) -> None:
          """ Save the model to disk.
  
          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.
 
</s> remove         self._io.save()  # pylint:disable=protected-access
 </s> add         self._io.save(is_exit=is_exit) </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: </s> remove     def save(self) -> None:
 </s> add     def save(self, is_exit: bool = False) -> None:
    def save(self, is_exit: bool = False) -> None:
                  continue
              model.summary(line_length=100, print_fn=print_fn)
          parent.summary(line_length=100, print_fn=print_fn)
  
    def save(self, is_exit: bool = False) -> None:
          """ Save the model to disk.
  
          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.
keep keep keep keep replace keep keep keep keep keep
 Training: Add setting option to save optimizer weights 
plugins/train/model/_base/model.py