              print(e)
              return False
  
      def save_weights(self):
          self.encoder.save_weights(self.model_dir + encoderH5)
          self.decoder_A.save_weights(self.model_dir + decoder_AH5)
          self.decoder_B.save_weights(self.model_dir + decoder_BH5)
          print('saved model weights')
  
  class TrainerAE():
      random_transform_args = {
          'rotation_range': 10,
 
</s> remove             self.encoder.load_weights(self.model_dir + encoderH5)
            self.decoder_A.load_weights(self.model_dir + face_A)
            self.decoder_B.load_weights(self.model_dir + face_B)
 </s> add             self.encoder.load_weights(self.model_dir / encoderH5)
            self.decoder_A.load_weights(self.model_dir / face_A)
            self.decoder_B.load_weights(self.model_dir / face_B)
 </s> remove             output_file = self.output_dir / Path(filename).stem
 </s> add             output_file = get_folder(self.output_dir) / Path(filename).stem </s> remove         if faces_count > 0 and self.arguments.verbose:
 </s> add         if faces_count > 1 and self.arguments.verbose: </s> remove             faces_count +=1
 </s> add             faces_count += 1
        self.encoder.save_weights(self.model_dir / encoderH5)
        self.decoder_A.save_weights(self.model_dir / decoder_AH5)
        self.decoder_B.save_weights(self.model_dir / decoder_BH5)

              print(e)
              return False
  
      def save_weights(self):
        self.encoder.save_weights(self.model_dir / encoderH5)
        self.decoder_A.save_weights(self.model_dir / decoder_AH5)
        self.decoder_B.save_weights(self.model_dir / decoder_BH5)
        self.encoder.save_weights(self.model_dir / encoderH5)
        self.decoder_A.save_weights(self.model_dir / decoder_AH5)
        self.decoder_B.save_weights(self.model_dir / decoder_BH5)
        self.encoder.save_weights(self.model_dir / encoderH5)
        self.decoder_A.save_weights(self.model_dir / decoder_AH5)
        self.decoder_B.save_weights(self.model_dir / decoder_BH5)
          print('saved model weights')
  
  class TrainerAE():
      random_transform_args = {
          'rotation_range': 10,
keep keep keep keep replace replace replace keep keep keep keep keep
 Changes I forgot to push :-/ (#136) 
lib/ModelAE.py