              The face filenames as keys with the zip compressed mask as value.
          """
          logger.trace("side: %s, detected_faces: %s, area: %s", side, detected_faces, area)
          masks = dict()
          if self._alignments_version[side] == 1.0:
              centering = "legacy"
              size = self._training_sizes[side]
          else:
              centering = self._config["centering"]
              size = list(self._aligned_faces[side].values())[0].get_cropped_size(centering)
          for fhash, face in detected_faces.items():
              mask = partial(face.get_landmark_mask,
                             size,
                             area,
                             aligned=True,
 
</s> remove             size = self._training_sizes[side]
            centering = "legacy" if self._alignments_version[side] == 1.0 else "head"
            logger.debug("side: %s, centering: %s", side, centering)
 </s> add  </s> remove                            centering=centering,
 </s> add                            centering=self._config["centering"], </s> remove                 face.load_aligned(None, size=size, centering=centering)
 </s> add                 face.aligned = AlignedFace(face.landmarks_xy,
                                           centering=self._config["centering"],
                                           size=size,
                                           is_aligned=True) </s> remove         cropped = np.zeros((batch.shape[0], size, size, batch.shape[3]), dtype=batch.dtype)

        for out, align, img in zip(cropped, aligned, batch):
            slices = align.get_cropped_slices(self._config["centering"])
            out[slices["out"][0], slices["out"][1], :] = img[slices["in"][0], slices["in"][1], :]
 </s> add         cropped = np.array([align.extract_face(img) for align, img in zip(aligned, batch)])
        size = list(self._aligned_faces[side].values())[0].size
              The face filenames as keys with the zip compressed mask as value.
          """
          logger.trace("side: %s, detected_faces: %s, area: %s", side, detected_faces, area)
          masks = dict()
        size = list(self._aligned_faces[side].values())[0].size
        size = list(self._aligned_faces[side].values())[0].size
        size = list(self._aligned_faces[side].values())[0].size
        size = list(self._aligned_faces[side].values())[0].size
        size = list(self._aligned_faces[side].values())[0].size
        size = list(self._aligned_faces[side].values())[0].size
          for fhash, face in detected_faces.items():
              mask = partial(face.get_landmark_mask,
                             size,
                             area,
                             aligned=True,
keep keep keep keep replace replace replace replace replace replace keep keep keep keep keep
 Bugfix - Warp to landmarks 
plugins/train/trainer/_base.py