              exit(0)
          except Exception as err:
              raise err
  
      def load_model(self):
          """ Load the model requested for training """
          logger.debug("Loading Model")
          model_dir = get_folder(self.args.model_dir)
          configfile = self.args.configfile if hasattr(self.args, "configfile") else None
          augment_color = not self.args.no_augment_color
          model = PluginLoader.get_model(self.trainer_name)(
 
</s> remove         model_dir = get_folder(self.args.model_dir)
        configfile = self.args.configfile if hasattr(self.args, "configfile") else None
        augment_color = not self.args.no_augment_color
 </s> add         model_dir = get_folder(self._args.model_dir)
        configfile = self._args.configfile if hasattr(self._args, "configfile") else None
        augment_color = not self._args.no_augment_color </s> remove             gpus=self.args.gpus,
 </s> add             gpus=self._args.gpus, </s> remove                 with self.lock:
                    self.preview_buffer[name] = image
 </s> add                 with self._lock:
                    self._preview_buffer[name] = image </s> remove                 self.model.do_snapshot()
 </s> add                 self._model.do_snapshot() </s> remove     def load_trainer(self, model):
        """ Load the trainer requested for training """
 </s> add         Returns
        -------
        :file:`plugins.train.trainer` plugin
            The requested model trainer plugin
        """
    def _load_model(self):
        """ Load the model requested for training.

        Returns
        -------
        :file:`plugins.train.model` plugin
            The requested model plugin
        """
              exit(0)
          except Exception as err:
              raise err
  
    def _load_model(self):
        """ Load the model requested for training.

        Returns
        -------
        :file:`plugins.train.model` plugin
            The requested model plugin
        """
    def _load_model(self):
        """ Load the model requested for training.

        Returns
        -------
        :file:`plugins.train.model` plugin
            The requested model plugin
        """
          logger.debug("Loading Model")
          model_dir = get_folder(self.args.model_dir)
          configfile = self.args.configfile if hasattr(self.args, "configfile") else None
          augment_color = not self.args.no_augment_color
          model = PluginLoader.get_model(self.trainer_name)(
keep keep keep keep replace 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