          encoder_b = [encoder(input_b)]
  
          outputs = [self.decoder("a")(encoder_a), self.decoder("b")(encoder_b)]
  
          autoencoder = KerasModel(inputs, outputs, name=self.name)
          return autoencoder
  
      def encoder(self):
          """ The original Faceswap Encoder Network.
  
 
</s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name) </s> remove         autoencoder = KerasModel(inputs, outputs, name=self.name)
 </s> add         autoencoder = KerasModel(inputs, outputs, name=self.model_name)
        autoencoder = KerasModel(inputs, outputs, name=self.model_name)

          encoder_b = [encoder(input_b)]
  
          outputs = [self.decoder("a")(encoder_a), self.decoder("b")(encoder_b)]
  
        autoencoder = KerasModel(inputs, outputs, name=self.model_name)
          return autoencoder
  
      def encoder(self):
          """ The original Faceswap Encoder Network.
  
keep keep keep keep replace keep keep keep keep keep
 Bugfix -Weights freezing/loading for dfl-sae 
plugins/train/model/original.py