          var_x = Dense(self.encoder_dim)(Flatten()(var_x))
          var_x = Dense(8 * 8 * self.encoder_dim)(var_x)
          var_x = Reshape((8, 8, self.encoder_dim))(var_x)
          var_x = UpscaleBlock(self.encoder_dim)(var_x)
          return KerasModel(input_, var_x, name=self.name)
  
      def decoder(self, side):
          """ DFL H128 Decoder """
          input_ = Input(shape=(16, 16, self.encoder_dim))
          var_x = input_
 
</s> remove             logger.info("Updating legacy weights from '%s'...", model_name)
 </s> add  </s> remove                      size, points, dilation, blur_kernel)
 </s> add                      self.__class__.__name__, size, points, dilation, blur_kernel)
        return KerasModel(input_, var_x, name="encoder")
          var_x = Dense(self.encoder_dim)(Flatten()(var_x))
          var_x = Dense(8 * 8 * self.encoder_dim)(var_x)
          var_x = Reshape((8, 8, self.encoder_dim))(var_x)
          var_x = UpscaleBlock(self.encoder_dim)(var_x)
        return KerasModel(input_, var_x, name="encoder")
  
      def decoder(self, side):
          """ DFL H128 Decoder """
          input_ = Input(shape=(16, 16, self.encoder_dim))
          var_x = input_
keep keep keep keep replace keep keep keep keep keep
 Bugfixes:
  - dfl_h128 Legacy Weights update
  - lib.faces_detect - Logging fix 
plugins/train/model/dfl_h128.py