              self.decoder_B.load_weights(os.path.join(self.model_dir, face_B))
              print('loaded model weights')
              return True
          except Exception as e:
              print('Failed loading existing training data.')
              print(e)
              return False        
  
      def converter(self, swap):
          autoencoder = self.autoencoder_B if not swap else self.autoencoder_A
          return autoencoder.predict
 
</s> remove     def conv(self, filters, kernel_size=4, strides=2):
 </s> add     
    def conv(self, filters, kernel_size=5, strides=2, **kwargs): </s> remove             return self._model_nomen
 </s> add             return self._model_name </s> remove             self._model_nomen = self._model_nomen = os.path.split(os.path.dirname(__file__))[1].replace("Model_", "")            
        return self._model_nomen
 </s> add             self._model_name = os.path.split(os.path.dirname(__file__))[1].replace("Model_", "")            
        return self._model_name </s> remove             x = Conv2D(filters, kernel_size=kernel_size, strides=strides, padding='same')(x)         
 </s> add             x = Conv2D(filters, kernel_size=kernel_size, strides=strides, kernel_initializer=conv_init, padding='same', **kwargs)(x)          </s> remove         Encoder = getattr(self, "Encoder") if not ENCODER else getattr(self, "Encoder_{}".format(ENCODER))
 </s> add         Encoder = getattr(self, "Encoder_{}".format(self._encoder_type.value))
        Decoder = getattr(self, "Decoder_{}".format(self._encoder_type.value))
            print('Failed loading existing training data.', e)
              self.decoder_B.load_weights(os.path.join(self.model_dir, face_B))
              print('loaded model weights')
              return True
          except Exception as e:
            print('Failed loading existing training data.', e)
            print('Failed loading existing training data.', e)
              return False        
  
      def converter(self, swap):
          autoencoder = self.autoencoder_B if not swap else self.autoencoder_A
          return autoencoder.predict
keep keep keep keep replace replace keep keep keep keep keep
 model update (#417)

New, functional Original 128 model 
plugins/Model_OriginalHighRes/Model.py