          var_x = Flatten()(var_x)
      return var_x
  
  
  def _get_upscale_layer(method: str,
                         filters: int,
                         activation: Optional[str] = None,
                         upsamples: Optional[int] = None,
                         interpolation: Optional[str] = None) -> keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
 
</s> remove                  activation: str = "leakyrelu",
 </s> add                  activation: Optional[str] = "leakyrelu", </s> remove             var_x = LeakyReLU(alpha=0.1)(var_x)
 </s> add             if not self._is_dny:
                var_x = LeakyReLU(alpha=0.1)(var_x) </s> remove             var_x = Conv2DBlock(filters, activation="leakyrelu", name=f"fs_enc_convblk_{i}")(var_x)
 </s> add             name = f"fs_{'dny_' if self._is_alt else ''}enc"
            var_x = Conv2DBlock(filters,
                                kernel_size=self._kernel_size,
                                strides=self._strides,
                                relu_alpha=self._relu_alpha,
                                name=f"{name}_convblk_{i}")(var_x)
def _get_upscale_layer(method: Literal["resize_images", "subpixel", "upscale_dny", "upscale_fast",
                                       "upscale_hybrid", "upsample2d"],
          var_x = Flatten()(var_x)
      return var_x
  
  
def _get_upscale_layer(method: Literal["resize_images", "subpixel", "upscale_dny", "upscale_fast",
                                       "upscale_hybrid", "upsample2d"],
                         filters: int,
                         activation: Optional[str] = None,
                         upsamples: Optional[int] = None,
                         interpolation: Optional[str] = None) -> keras.layers.Layer:
      """ Obtain an instance of the requested upscale method.
keep keep keep keep replace keep keep keep keep keep
 Phaze-A - Updates for future implementations 
plugins/train/model/phaze_a.py