      def load(self, swapped):
          (face_A,face_B) = (decoder_AH5, decoder_BH5) if not swapped else (decoder_BH5, decoder_AH5)
  
          try:
              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)
              print('loaded model weights')
              return True
          except Exception as e:
              print('Failed loading existing training data.')
              print(e)
 
</s> remove         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)
 </s> add         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)
 </s> remove             
            if not self.check_skipframe(filename): # process as normal
                for idx, face in faces:
                    image = converter.patch_image(image, face)

            output_file = self.output_dir / Path(filename).name
 </s> add  </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:
            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)

      def load(self, swapped):
          (face_A,face_B) = (decoder_AH5, decoder_BH5) if not swapped else (decoder_BH5, decoder_AH5)
  
          try:
            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)
            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)
            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)
              print('loaded model weights')
              return True
          except Exception as e:
              print('Failed loading existing training data.')
              print(e)
keep keep keep keep replace replace replace keep keep keep keep keep
 Changes I forgot to push :-/ (#136) 
lib/ModelAE.py