              self.autoencoder_B = multi_gpu_model( self.autoencoder_B , self.gpus)
          
          
          self.autoencoder_A.compile(optimizer=optimizer, loss='mean_absolute_error')
          self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')                    
          
          
      def load(self, swapped):        
          model_dir = str(self.model_dir)
          
          from json import JSONDecodeError
          face_A, face_B = (hdf['decoder_AH5'], hdf['decoder_BH5']) if not swapped else (hdf['decoder_BH5'], hdf['decoder_AH5'])
          
 
</s> remove             print('Error loading training info:', e.msg)
            self._epoch_no = 0   
        
        (face_A,face_B) = (hdf['decoder_AH5'], hdf['decoder_BH5']) if not swapped else (hdf['decoder_BH5'], hdf['decoder_AH5'])                
 </s> add             logger.warning('Error loading training info: %s', str(e.msg))
            self._epoch_no = 0

        (face_A,face_B) = (hdf['decoder_AH5'], hdf['decoder_BH5']) if not swapped else (hdf['decoder_BH5'], hdf['decoder_AH5'])
 </s> remove             print ("Generator weights files not found.")
 </s> add             logger.info("Generator weights files not found.")
 </s> remove             print ("Generator weights files not found.")
 </s> add             logger.info("Generator weights files not found.")
 </s> remove             print("swapping not supported on GAN")
 </s> add             logger.warning("swapping not supported on GAN")
 </s> remove             print("swapping not supported on GAN")
 </s> add             logger.warning("swapping not supported on GAN")

        self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')


    def load(self, swapped):
              self.autoencoder_B = multi_gpu_model( self.autoencoder_B , self.gpus)
          
          
          self.autoencoder_A.compile(optimizer=optimizer, loss='mean_absolute_error')
        self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')


    def load(self, swapped):
        self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')


    def load(self, swapped):
        self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')


    def load(self, swapped):
        self.autoencoder_B.compile(optimizer=optimizer, loss='mean_absolute_error')


    def load(self, swapped):
          model_dir = str(self.model_dir)
          
          from json import JSONDecodeError
          face_A, face_B = (hdf['decoder_AH5'], hdf['decoder_BH5']) if not swapped else (hdf['decoder_BH5'], hdf['decoder_AH5'])
          
keep keep keep keep replace replace replace replace keep keep keep keep keep
 Logging (#541)

* Convert prints to logger. Further logging improvements. Tidy  up

* Fix system verbosity. Allow SystemExit

* Fix reload extract bug

* Child Traceback handling

* Safer shutdown procedure

* Add shutdown event to queue manager

* landmarks_as_xy > property. GUI notes + linting. Aligner bugfix

* fix FaceFilter. Enable nFilter when no Filter is supplied

* Fix blurry face filter

* Continue on IO error. Better error handling

* Explicitly print stack trace tocrash log

* Windows Multiprocessing bugfix

* Add git info and conda version to crash log

* Windows/Anaconda mp bugfix

* Logging fixes for training 
plugins/model/Model_OriginalHighRes/Model.py