  
      def build_autoencoders(self):
          """ Initialize IAE model """
          logger.debug("Initializing model")
          inputs = [Input(shape=self.input_shape, name="face")]
          if self.config.get("mask_type", None):
              mask_shape = (self.input_shape[:2] + (1, ))
              inputs.append(Input(shape=mask_shape, name="mask"))
  
          decoder = self.networks["decoder"].network
          encoder = self.networks["encoder"].network
          inter_both = self.networks["inter"].network
          for side in ("a", "b"):
              inter_side = self.networks["intermediate_{}".format(side)].network
 
</s> remove         inputs = [Input(shape=self.input_shape, name="face")]
        if self.config.get("mask_type", None):
            mask_shape = (self.input_shape[:2] + (1, ))
            inputs.append(Input(shape=mask_shape, name="mask"))

 </s> add  </s> remove     def build_autoencoders(self):
 </s> add     def build_autoencoders(self, inputs): </s> remove         inputs = [Input(shape=self.input_shape, name="face")]
        if self.config.get("mask_type", None):
            mask_shape = self.config["output_size"], self.config["output_size"], 1
            inputs.append(Input(shape=mask_shape, name="mask"))

 </s> add  </s> remove     def build_autoencoders(self):
 </s> add     def build_autoencoders(self, inputs):
 </s> remove     def build_autoencoders(self):
        """ Initialize Dfaker model """
        logger.debug("Initializing model")
        inputs = [Input(shape=self.input_shape, name="face")]
        if self.config.get("mask_type", None):
            mask_shape = (self.input_shape[0] * 2, self.input_shape[1] * 2, 1)
            inputs.append(Input(shape=mask_shape, name="mask"))

        for side in ("a", "b"):
            decoder = self.networks["decoder_{}".format(side)].network
            output = decoder(self.networks["encoder"].network(inputs[0]))
            autoencoder = KerasModel(inputs, output)
            self.add_predictor(side, autoencoder)
        logger.debug("Initialized model")

 </s> add 
  
      def build_autoencoders(self):
          """ Initialize IAE model """
          logger.debug("Initializing model")





          decoder = self.networks["decoder"].network
          encoder = self.networks["encoder"].network
          inter_both = self.networks["inter"].network
          for side in ("a", "b"):
              inter_side = self.networks["intermediate_{}".format(side)].network
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Model Structure Changes

Standardize inputs for AutoEncoders
Name outputs from AutoEncoders
Name layers in nn_blocks.py 
plugins/train/model/iae.py