              if not self.args.redirect_gui:
                  msg += " If you want to kill it now, press Ctrl + c"
              log = logger.info
          log(msg)
          self.stop = True
          thread.join()
          sys.stdout.flush()
          logger.debug("Ended Training thread")
  
      def training(self):
 
</s> remove             if not self.args.redirect_gui:
 </s> add             if not self._args.redirect_gui: </s> remove         logger.debug("Ended Training thread")
 </s> add         logger.debug("Ended training thread") </s> remove     def training(self):
        """ The training process to be run inside a thread """
 </s> add     def _training(self):
        """ The training process to be run inside a thread. """ </s> remove     def end_thread(self, thread, err):
        """ On termination output message and join thread back to main """
 </s> add     def _end_thread(self, thread, err):
        """ Output message and join thread back to main on termination.

        Parameters
        ----------
        thread: :class:`lib.multithreading.MultiThread`
            The background training thread
        err: bool
            Whether an error has been detected in :func:`_monitor`
        """ </s> remove         self.stop = True
 </s> add         self._stop = True
        self._stop = True
              if not self.args.redirect_gui:
                  msg += " If you want to kill it now, press Ctrl + c"
              log = logger.info
          log(msg)
        self._stop = True
          thread.join()
          sys.stdout.flush()
          logger.debug("Ended Training thread")
  
      def training(self):
keep keep keep keep replace keep keep keep keep keep
 Smart Masks - Training Implementation (#914)

* Smart Masks - Training

- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code

* Update mask helptext in cli.py

* Fix Warp to Landmarks
Remove SHA1 hashing from training data

* Update mask training config

* Capture missing masks at training init

* lib.image.read_image_batch - Return filenames with batch for ordering

* scripts.train - Documentation

* plugins.train.trainer - documentation

* Ensure backward compatibility.
Fix convert for new predicted masks

* Update removed masks to components for legacy models. 
scripts/train.py