          self._dense_recursions = 3
          logger.debug("Initialized: %s", self.__class__.__name__)
  
      @classmethod
      def _g_block(cls, inputs: Tensor, style: Tensor, filters: int, recursions: int = 2) -> Tensor:
          """ G_block adapted from ADAIN StyleGAN.
  
          Parameters
          ----------
          inputs: tensor
 
</s> remove             var_x = Reshape(new_shape)(var_x)
 </s> add             var_x = kl.Reshape(new_shape)(var_x) </s> remove         self._inputs = [Input(shape=shape) for shape in input_shapes]
 </s> add         self._inputs = [kl.Input(shape=shape) for shape in input_shapes] </s> remove                        inputs: Tensor,
 </s> add                        inputs: tf.Tensor, </s> remove def _bottleneck(inputs: Tensor, bottleneck: str, size: int, normalization: str) -> Tensor:
 </s> add def _bottleneck(inputs: tf.Tensor, bottleneck: str, size: int, normalization: str) -> tf.Tensor: </s> remove                        is_mask: bool = False) -> Tensor:
 </s> add                        is_mask: bool = False) -> tf.Tensor:
    def _g_block(cls,
                 inputs: tf.Tensor,
                 style: tf.Tensor,
                 filters: int,
                 recursions: int = 2) -> tf.Tensor:
          self._dense_recursions = 3
          logger.debug("Initialized: %s", self.__class__.__name__)
  
      @classmethod
    def _g_block(cls,
                 inputs: tf.Tensor,
                 style: tf.Tensor,
                 filters: int,
                 recursions: int = 2) -> tf.Tensor:
          """ G_block adapted from ADAIN StyleGAN.
  
          Parameters
          ----------
          inputs: tensor
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