  
      def _get_encoder_model(self):
          """ Return the model defined by the selected architecture.
  
          Parameters
          ----------
          input_shape: tuple
              The input shape for the model
  
          Returns
          -------
          :class:`keras.Model`
              The selected keras model for the chosen encoder architecture
          """
 
</s> remove     def _get_encoder_model(self):
 </s> add     def _get_encoder_model(self) -> keras.models.Model: </s> remove         if self._selected_model.get("keras_name"):
            kwargs = self._selected_model["kwargs"]
 </s> add         model, kwargs = self._selected_model
        if model.keras_name: </s> remove     def __init__(self, input_shape, config):
 </s> add     def __init__(self, input_shape: Tuple[int, int, int], config: dict) -> None: </s> remove     def _selected_model(self):
        """ dict: The selected encoder model options dictionary """
 </s> add     def _selected_model(self) -> Tuple[_EncoderInfo, dict]:
        """ tuple(dict, :class:`_EncoderInfo`): The selected encoder model and it's associated
        keyword arguments """ </s> remove     def __init__(self, side, input_shape, config):
 </s> add     def __init__(self,
                 side: Literal["a", "b", "both"],
                 input_shape: Tuple[int, int, int],
                 config: dict) -> None:
  
      def _get_encoder_model(self):
          """ Return the model defined by the selected architecture.
  





          Returns
          -------
          :class:`keras.Model`
              The selected keras model for the chosen encoder architecture
          """
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Model updates
- Increase model summary width
- Phaze A updates
  - Update some min/max values
  - Add Decoder Filter Slope Mode
  - Add additional arguments for Upsampling2D
  - Adjust upsampling method for multiple upsamples in FC layers
  - Typing 
plugins/train/model/phaze_a.py