          decoder_b = self.decoder_b if self.details > 0 else self.decoder_b_fast
  
          outputs = [self.decoder_a()(encoder_a), decoder_b()(encoder_b)]
  
          autoencoder = KerasModel(inputs, outputs, name=self.name)
          return autoencoder
  
      def encoder(self):
          """ DeLight Encoder Network """
          input_ = Input(shape=self.input_shape)
 
</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                                  name="{}_{}".format(self.name, self.architecture))
 </s> add                                  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)
          decoder_b = self.decoder_b if self.details > 0 else self.decoder_b_fast
  
          outputs = [self.decoder_a()(encoder_a), decoder_b()(encoder_b)]
  
        autoencoder = KerasModel(inputs, outputs, name=self.model_name)
          return autoencoder
  
      def encoder(self):
          """ DeLight Encoder Network """
          input_ = Input(shape=self.input_shape)
keep keep keep keep replace keep keep keep keep keep
 Bugfix -Weights freezing/loading for dfl-sae 
plugins/train/model/dlight.py