          outputs = [decoders["a"], decoders["b"]]
          autoencoder = KerasModel(inputs, outputs, name=self.model_name)
          return autoencoder
  
      def _build_encoders(self, inputs):
          """ Build the encoders for Phaze-A
  
          Parameters
          ----------
          inputs: list
 
</s> remove     def _build_decoders(self, inputs):
 </s> add     def _build_decoders(
            self,
            inputs: Dict[str, Union[List[keras.models.Model], keras.models.Model]]
            ) -> Dict[str, keras.models.Model]: </s> remove     def _build_fully_connected(self, inputs):
 </s> add     def _build_fully_connected(
            self,
            inputs: Dict[str, keras.models.Model]) -> Dict[str, List[keras.models.Model]]: </s> remove     def __call__(self, inputs):
 </s> add     def __call__(self, inputs: Tensor) -> Tensor: </s> remove     def _normalization(self, inputs):
 </s> add     def _normalization(self, inputs: Tensor) -> Tensor: </s> remove     def build_model(self, inputs):
 </s> add     def build_model(self, inputs: List[Tensor]) -> keras.models.Model:
    def _build_encoders(self, inputs: List[Tensor]) -> Dict[str, keras.models.Model]:
          outputs = [decoders["a"], decoders["b"]]
          autoencoder = KerasModel(inputs, outputs, name=self.model_name)
          return autoencoder
  
    def _build_encoders(self, inputs: List[Tensor]) -> Dict[str, keras.models.Model]:
          """ Build the encoders for Phaze-A
  
          Parameters
          ----------
          inputs: list
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