      @property
      def adjusted_matrix(self):
          """ :class:`numpy.ndarray`: The 3x2 transformation matrix for extracting and aligning the
          core face area out of the original frame with padding and sizing applied. """
          with self._cache["adjusted_matrix"][1]:
              if self._cache["adjusted_matrix"][0] is None:
                  matrix = self.matrix.copy()
                  mat = matrix * (self._size - 2 * self.padding)
                  mat[:, 2] += self.padding
                  logger.trace("adjusted_matrix: %s", mat)
                  self._cache["adjusted_matrix"][0] = mat
 
</s> remove                 logger.trace("adjusted_matrix: %s", mat)
                self._cache["adjusted_matrix"][0] = mat
        return self._cache["adjusted_matrix"][0]
 </s> add                 logger.trace("adjusted_matrix: %s", mat)  # type: ignore
                self._cache.adjusted_matrix = mat
        return self._cache.adjusted_matrix </s> remove     def adjusted_matrix(self):
 </s> add     def adjusted_matrix(self) -> np.ndarray: </s> remove                 self._cache["pose"][0] = PoseEstimate(lms)
        return self._cache["pose"][0]
 </s> add                 self._cache.pose = PoseEstimate(lms)
        return self._cache.pose </s> remove         if self._matrices[self._centering] is None:
 </s> add         if not np.any(self._matrices[self._centering]): </s> remove     def matrix(self):
 </s> add     def matrix(self) -> np.ndarray:
        with self._cache.lock("adjusted_matrix"):
            if self._cache.adjusted_matrix is None:
      @property
      def adjusted_matrix(self):
          """ :class:`numpy.ndarray`: The 3x2 transformation matrix for extracting and aligning the
          core face area out of the original frame with padding and sizing applied. """
        with self._cache.lock("adjusted_matrix"):
            if self._cache.adjusted_matrix is None:
        with self._cache.lock("adjusted_matrix"):
            if self._cache.adjusted_matrix is None:
                  matrix = self.matrix.copy()
                  mat = matrix * (self._size - 2 * self.padding)
                  mat[:, 2] += self.padding
                  logger.trace("adjusted_matrix: %s", mat)
                  self._cache["adjusted_matrix"][0] = mat
keep keep keep keep replace replace keep keep keep keep keep
 lib.align.aligned_face updates
  - Typing
  - Legacy support for pre-aligned faces
  - Coverage support for pre-aligned faces
  - Standardized retrieval of sub-crops 
lib/align/aligned_face.py