                  self.save_now = False
          logger.debug("Training cycle complete")
          model.save_models()
          trainer.clear_tensorboard()
          self.stop = True
  
      def monitor(self, thread):
          """ Monitor the console, and generate + monitor preview if requested """
          is_preview = self.args.preview
          logger.debug("Launching Monitor")
 
</s> remove     def monitor(self, thread):
        """ Monitor the console, and generate + monitor preview if requested """
        is_preview = self.args.preview
 </s> add     def _monitor(self, thread):
        """ Monitor the background :func:`_training` thread for key presses and errors.

        Returns
        -------
        bool
            ``True`` if there has been an error in the background thread otherwise ``False``
        """
        is_preview = self._args.preview </s> remove                 self.save_now = False
 </s> add                 self._save_now = False </s> remove             elif self.save_now:
 </s> add             elif self._save_now: </s> remove                     self.save_now = True
 </s> add                     self._save_now = True </s> remove         self.args = arguments
        self.timelapse = self.set_timelapse()
        self.images = self.get_images()
        self.stop = False
        self.save_now = False
        self.preview_buffer = dict()
        self.lock = Lock()

        self.trainer_name = self.args.trainer
 </s> add         self._args = arguments
        self._timelapse = self._set_timelapse()
        self._images = self._get_images()
        self._stop = False
        self._save_now = False
        self._preview_buffer = dict()
        self._lock = Lock()

        self.trainer_name = self._args.trainer
        self._stop = True
                  self.save_now = False
          logger.debug("Training cycle complete")
          model.save_models()
          trainer.clear_tensorboard()
        self._stop = True
  
      def monitor(self, thread):
          """ Monitor the console, and generate + monitor preview if requested """
          is_preview = self.args.preview
          logger.debug("Launching Monitor")
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