  
          if penalized_loss and self._model.config["mouth_multiplier"] > 1:
              retval["masks_mouth"] = alignments.masks_mouth
  
          logger.debug({key: {k: len(v) for k, v in val.items()} for key, val in retval.items()})
          return retval
  
      def _set_tensorboard(self):
          """ Set up Tensorboard callback for logging loss.
  
 
</s> remove             retval[side] = self._to_detected_faces(alignments, side)
        logger.debug("Returning: %s", {k: len(v) for k, v in retval.items()})
        return retval
 </s> add             self._detected_faces[side] = self._to_detected_faces(alignments, side)
            self._alignments_version[side] = alignments.version
        logger.debug("alignments_versions: %s, detected_faces: %s, ", self._alignments_version,
                     {k: len(v) for k, v in self._detected_faces.items()}) </s> remove         if not any([self._model.config["learn_mask"],
                    penalized_loss,
                    self._model.config["eye_multiplier"] > 1,
                    self._model.config["mouth_multiplier"] > 1,
                    self._model.command_line_arguments.warp_to_landmarks]):
            return retval

 </s> add  </s> remove     def get_items(self, arguments):
        """ Set the correct items to process """
        retval = None
        if self.type == "frames":
            retval = Frames(arguments.frames_dir).items
        elif self.type == "faces":
            retval = Faces(arguments.faces_dir)
        return retval

 </s> add  </s> remove             self.queue_images(extractor)
 </s> add  </s> remove         encodings = self.vgg_face.predict(detected_face.aligned_face)
 </s> add         feed = AlignedFace(detected_face.landmarks_xy, image=image, size=224, centering="legacy")
        encodings = self.vgg_face.predict(feed.face)

        logger.debug({key: {k: v if isinstance(v, float) else len(v)
                            for k, v in val.items()}
                      for key, val in retval.items()})
  
          if penalized_loss and self._model.config["mouth_multiplier"] > 1:
              retval["masks_mouth"] = alignments.masks_mouth
  
        logger.debug({key: {k: v if isinstance(v, float) else len(v)
                            for k, v in val.items()}
                      for key, val in retval.items()})
          return retval
  
      def _set_tensorboard(self):
          """ Set up Tensorboard callback for logging loss.
  
keep keep keep keep replace keep keep keep keep keep
 Extract - Increase area and move centering (#1095)

* Extract
  - Implement aligner re-feeding
  - Add extract type to pipeline.ExtractMedia
  - Add pose annotation to debug
* Convert
  - implement centering
  - remove usage of feed and reference face properties
  - Remove distributed option from convert
  - Force update of alignments file on legacy receive
* Train
  - Resize preview image to model output size
  - Force legacy centering if centering does not exist in model's state file
  - Enable training on legacy face sets

* Alignments Tool
  - Update draw to include head/pose
  - Remove DFL drop + linting
  - Remove remove-frames job
  - remove align-eyes option
  - Update legacy masks to new extract type
  - Exit if attempting to merge version 1.0 alignments files with version 2.0 alignments files
  - Re-generate thumbnails on legacy upgrade
* Mask Tool
  - Update for new extract + bugfix full frame
* Manual Tool
  - Update to new extraction method
   - Disable legacy alignments,
   - extract box bugfix
   - extract faces - size to 512 and center on head
* Preview Tool
  - Display based on model centering
* Sort Tool
  - Use alignments for sort by face

* lib.aligner
  - Add Pose Class
  - Add AlignedFace Class
  - center _MEAN_FACE on x
  - Add meta information with versioning to alignments file
  - lib.aligner.get_align_matrix to use landmarks not face
  - Refactor aligned faces in lib.faces_detect
* lib.logger
  - larger file log padding
* lib.config
  - Fix global changeable_items
* lib.face_filter
  - Use new extracted face images
* lib.image
  - bump thumbnail default size to 96px 
plugins/train/trainer/_base.py