              self.decoder_B.load_weights(os.path.join(self.model_dir, face_B))
              print('loaded model weights')
              return True
          except Exception as e:
              print('Failed loading existing training data.', e)
              return False        
  
  
      def converter(self, swap):
          autoencoder = self.autoencoder_B if not swap else self.autoencoder_A
          return autoencoder.predict
      
 
</s> remove             self.encoder.load_weights(os.path.join(self.model_dir, hdf['encoderH5']))
            self.decoder_A.load_weights(os.path.join(self.model_dir, face_A))
            self.decoder_B.load_weights(os.path.join(self.model_dir, face_B))
 </s> add             self.encoder.load_weights(os.path.join(model_dir, hdf['encoderH5']))
            self.decoder_A.load_weights(os.path.join(model_dir, face_A))
            self.decoder_B.load_weights(os.path.join(model_dir, face_B)) </s> remove         except (JSONDecodeError, IOError) as e:
            print('Failed loading training state metadata', e)
            self._epoch_no = 0        
 </s> add         except IOError as e:
            print('Error loading training info:', e.strerror)
            self._epoch_no = 0
        except JSONDecodeError as e:
            print('Error loading training info:', e.msg)
            self._epoch_no = 0                          </s> remove         state_dir = os.path.join(self.model_dir, 'state_{version_str}_{ENCODER.value}.json'.format(**globals()))
 </s> add         state_dir = os.path.join(model_dir, 'state_{version_str}_{ENCODER.value}.json'.format(**globals())) </s> remove     def load(self, swapped):
 </s> add     def load(self, swapped):        
        model_dir = str(self.model_dir)
        
            print('Failed loading training data:', str(e))            
      
        return False
              self.decoder_B.load_weights(os.path.join(self.model_dir, face_B))
              print('loaded model weights')
              return True
          except Exception as e:
            print('Failed loading training data:', str(e))            
      
        return False
            print('Failed loading training data:', str(e))            
      
        return False
            print('Failed loading training data:', str(e))            
      
        return False
  
      def converter(self, swap):
          autoencoder = self.autoencoder_B if not swap else self.autoencoder_A
          return autoencoder.predict
      
keep keep keep keep replace replace replace keep keep keep keep keep
 fixed Windows 10 path error while loading weights (#442) 
plugins/Model_OriginalHighRes/Model.py