                                       self._feeder,
                                       self._images)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def _get_config(self, configfile):
          """ Get the saved training config options. Override any global settings with the setting
          provided from the model's saved config.
  
          Parameters
          -----------
 
</s> remove                                      self._config.get("preview_images", 14),
 </s> add                                      int(self._config.get("preview_images", 14)), </s> remove         saver: lib.images.ImagesSaver
            The background saver for saving the image
 </s> add         saver: :class:`lib.images.ImagesSaver` or ``None``
            The background saver for saving the image or ``None`` if faces are not to be saved </s> remove     def get_batch(self):
 </s> add     def get_batch(self) -> Tuple[List[List[np.ndarray]], ...]: </s> remove             retval[side] = self._load_generator(idx).minibatch_ab(self._images[side],
                                                                  batchsize,
                                                                  side,
                                                                  do_shuffle=True,
                                                                  is_preview=True)
        logger.debug("Set preview feed. Batchsize: %s", batchsize)
 </s> add             retval[side] = self._load_generator(side,
                                                True,
                                                batch_size=batchsize).minibatch_ab() </s> remove     def initialize(self, training_size):
 </s> add     def _get_constants(self) -> AugConstants:
    def _get_config(self, configfile: Optional[str]) -> ConfigType:
                                       self._feeder,
                                       self._images)
          logger.debug("Initialized %s", self.__class__.__name__)
  
    def _get_config(self, configfile: Optional[str]) -> ConfigType:
          """ Get the saved training config options. Override any global settings with the setting
          provided from the model's saved config.
  
          Parameters
          -----------
keep keep keep keep replace keep keep keep keep keep
 Data Augmentation update (#1263)

- lib.detected_face
    - Subclass Masks for Landmark based masks
    - Add training mask propery + methods to DetectedFace
  - lib.training_training
    - subclass TrainingDataGenerator for training and preview data
    - Split cache into own module
    - Reduce thread count to 1 to prevent image corruption + data re-use
    - Process on largest model input/output size rather than stored image size
    - Size and crop masks during caching stage
    - Implement ring buffer for data flow
    - Fix preview reload bug
  - augmentation
    - typing
    - switch color aug order
    - better initialization
    - Fix warp + landmark warp to correctly apply at different image scales
    - Slightly improved warp caching
    - Don't store whether image is_preview. Handle all data as training images implicitly
  - plugins.trainer: Typing and fixes to work with trainingdata refactor 
plugins/train/trainer/_base.py