          self._depth = config[f"{self._type}_depth"]
          self._min_filters = config["fs_original_min_filters"]
          self._max_filters = config["fs_original_max_filters"]
  
      def __call__(self, inputs: Tensor) -> Tensor:
          """ Call the original Faceswap Encoder
  
 
</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 def _get_upscale_layer(method: str,
 </s> add def _get_upscale_layer(method: Literal["resize_images", "subpixel", "upscale_dny", "upscale_fast",
                                       "upscale_hybrid", "upsample2d"], </s> remove                  activation: str = "leakyrelu",
 </s> add                  activation: Optional[str] = "leakyrelu",
        self._is_alt = config["fs_original_use_alt"]
        self._relu_alpha = 0.2 if self._is_alt else 0.1
        self._kernel_size = 3 if self._is_alt else 5
        self._strides = 1 if self._is_alt else 2
          self._depth = config[f"{self._type}_depth"]
          self._min_filters = config["fs_original_min_filters"]
          self._max_filters = config["fs_original_max_filters"]
        self._is_alt = config["fs_original_use_alt"]
        self._relu_alpha = 0.2 if self._is_alt else 0.1
        self._kernel_size = 3 if self._is_alt else 5
        self._strides = 1 if self._is_alt else 2
  
      def __call__(self, inputs: Tensor) -> Tensor:
          """ Call the original Faceswap Encoder
  
keep keep add keep keep keep keep
 Phaze-A - Updates for future implementations 
plugins/train/model/phaze_a.py