              var_x = Reshape(new_shape)(var_x)
          return var_x
  
      def _upscale_block(self,
                         inputs: Tensor,
                         filters: int,
                         skip_residual: bool = False,
                         is_mask: bool = False) -> Tensor:
          """ Upscale block for Phaze-A Decoder.
  
 
</s> remove                        is_mask: bool = False) -> Tensor:
 </s> add                        is_mask: bool = False) -> tf.Tensor: </s> remove             var_x = Reshape(new_shape)(var_x)
 </s> add             var_x = kl.Reshape(new_shape)(var_x) </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                 var_x = LeakyReLU(alpha=0.1)(var_x)
 </s> add                 var_x = kl.LeakyReLU(alpha=0.1)(var_x) </s> remove             var_x = GaussianNoise(1.0)(var_x)
 </s> add             var_x = kl.GaussianNoise(1.0)(var_x)
                       inputs: tf.Tensor,
              var_x = Reshape(new_shape)(var_x)
          return var_x
  
      def _upscale_block(self,
                       inputs: tf.Tensor,
                         filters: int,
                         skip_residual: bool = False,
                         is_mask: bool = False) -> Tensor:
          """ Upscale block for Phaze-A Decoder.
  
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