          retval = int(retval * self._config["fc_dimensions"] ** 2)
          return retval
  
      @property
      def _max_nodes(self):
          """ int: The number of nodes for the final Dense. For non g-block layers this will be the
          given maximum filters multiplied by the dimensions squared. This number will be scaled down
          if the final shape can not be mapped to the requested output size.
  
          For g-block layers, this is the given config value.
 
</s> remove     def _min_nodes(self):
 </s> add     def _min_nodes(self) -> int: </s> remove     def _scale_filters(self, original_filters):
 </s> add     def _scale_filters(self, original_filters: int) -> int: </s> remove     def _reshape_for_output(self, inputs):
 </s> add     def _reshape_for_output(self, inputs: Tensor) -> Tensor: </s> remove         rounding=128,
 </s> add         rounding=64, </s> remove     def _build_g_blocks(self, inputs):
 </s> add     def _build_g_blocks(
                self,
                inputs: Dict[str, List[keras.models.Model]]
            ) -> Dict[str, Union[List[keras.models.Model], keras.models.Model]]:
    def _max_nodes(self) -> int:
          retval = int(retval * self._config["fc_dimensions"] ** 2)
          return retval
  
      @property
    def _max_nodes(self) -> int:
          """ int: The number of nodes for the final Dense. For non g-block layers this will be the
          given maximum filters multiplied by the dimensions squared. This number will be scaled down
          if the final shape can not be mapped to the requested output size.
  
          For g-block layers, this is the given config value.
keep keep keep keep 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