                                           "upscale_fast", "upscale_hybrid", "upsample2d"],
                         filters: int,
                         activation: str | None = None,
                         upsamples: int | None = None,
                         interpolation: str | None = None) -> keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
  
      Parameters
      ----------
      method: str
 
</s> remove     bottleneck: str
        The type of layer to use for the bottleneck
 </s> add     bottleneck: str or ``None``
        The type of layer to use for the bottleneck. ``None`` to not use a bottleneck </s> remove     def __call__(self, inputs: Tensor | list[Tensor]) -> Tensor | list[Tensor]:
 </s> add     def __call__(self, inputs: tf.Tensor | list[tf.Tensor]) -> tf.Tensor | list[tf.Tensor]: </s> remove                        is_mask: bool = False) -> Tensor:
 </s> add                        is_mask: bool = False) -> 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             inputs = [inputs, Input(shape=self._input_shape)]
 </s> add             inputs = [inputs, kl.Input(shape=self._input_shape)]
                       interpolation: str | None = None) -> tf.keras.layers.Layer:
                                           "upscale_fast", "upscale_hybrid", "upsample2d"],
                         filters: int,
                         activation: str | None = None,
                         upsamples: int | None = None,
                       interpolation: str | None = None) -> tf.keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
  
      Parameters
      ----------
      method: str
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