      def _upscale_block(self,
                         inputs: Tensor,
                         filters: int,
                         skip_residual: bool = False,
                         is_mask: bool = False) -> Tensor:
          """ Upscale block for Phaze-A Decoder.
  
          Uses requested upscale method, adds requested regularization and activation function.
  
          Parameters
 
</s> remove                        inputs: Tensor,
 </s> add                        inputs: tf.Tensor, </s> remove     def _g_block(cls, inputs: Tensor, style: Tensor, filters: int, recursions: int = 2) -> Tensor:
 </s> add     def _g_block(cls,
                 inputs: tf.Tensor,
                 style: tf.Tensor,
                 filters: int,
                 recursions: int = 2) -> tf.Tensor: </s> remove                        interpolation: str | None = None) -> keras.layers.Layer:
 </s> add                        interpolation: str | None = None) -> tf.keras.layers.Layer: </s> remove             var_x = Reshape(new_shape)(var_x)
 </s> add             var_x = kl.Reshape(new_shape)(var_x) </s> remove     def _reshape_for_output(self, inputs: Tensor) -> Tensor:
 </s> add     def _reshape_for_output(self, inputs: tf.Tensor) -> tf.Tensor:
                       is_mask: bool = False) -> tf.Tensor:
      def _upscale_block(self,
                         inputs: Tensor,
                         filters: int,
                         skip_residual: bool = False,
                       is_mask: bool = False) -> tf.Tensor:
          """ Upscale block for Phaze-A Decoder.
  
          Uses requested upscale method, adds requested regularization and activation function.
  
          Parameters
keep keep keep keep replace keep keep keep keep keep
 Updates:
    - Remove clipfaker
    - Add clip to Phaze-A
    - streamline clip to vision only
    - update lib.model.networks
    - Docs and tests update
    - Phaze-A - add option to flatten bottleneck 
plugins/train/model/phaze_a.py