  
          for iteration in range(0, self.args.iterations):
              logger.trace("Training iteration: %s", iteration)
              save_iteration = iteration % self.args.save_interval == 0
              viewer = display_func if save_iteration or self.save_now else None
              timelapse = self.timelapse if save_iteration else None
              trainer.train_one_step(viewer, timelapse)
              if self.stop:
 
</s> remove             elif save_iteration:
 </s> add             if save_iteration: </s> remove                     model.save_models()
 </s> add                     model.save_models(snapshot_iteration) </s> remove         model.save_models()
 </s> add         model.save_models(False)
            snapshot_interval = self.args.save_interval * self.args.snapshot_interval
            snapshot_iteration = bool(snapshot_interval != 0 and
                                      iteration >= snapshot_interval and
                                      iteration % snapshot_interval == 0)
  
          for iteration in range(0, self.args.iterations):
              logger.trace("Training iteration: %s", iteration)
            snapshot_interval = self.args.save_interval * self.args.snapshot_interval
            snapshot_iteration = bool(snapshot_interval != 0 and
                                      iteration >= snapshot_interval and
                                      iteration % snapshot_interval == 0)
              save_iteration = iteration % self.args.save_interval == 0
              viewer = display_func if save_iteration or self.save_now else None
              timelapse = self.timelapse if save_iteration else None
              trainer.train_one_step(viewer, timelapse)
              if self.stop:
keep keep add keep keep keep keep keep
 Add save snapshot backup option for training 
scripts/train.py