              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
          return self._cache["adjusted_matrix"][0]
  
      @property
      def face(self):
          """ :class:`numpy.ndarray`: The aligned face at the given :attr:`size` at the specified
          :attr:`coverage` in the given :attr:`dtype`. If an :attr:`image` has not been provided
 
</s> remove     def face(self):
 </s> add     def face(self) -> Optional[np.ndarray]: </s> remove         with self._cache["adjusted_matrix"][1]:
            if self._cache["adjusted_matrix"][0] is None:
 </s> add         with self._cache.lock("adjusted_matrix"):
            if self._cache.adjusted_matrix is None: </s> remove     logger.trace("image shape: %s, matrix: %s, size: %s. padding: %s",
 </s> add     logger.trace("image shape: %s, matrix: %s, size: %s. padding: %s",  # type: ignore </s> remove     def adjusted_matrix(self):
 </s> add     def adjusted_matrix(self) -> np.ndarray: </s> remove         if self._matrices[self._centering] is None:
 </s> add         if not np.any(self._matrices[self._centering]):
                logger.trace("adjusted_matrix: %s", mat)  # type: ignore
                self._cache.adjusted_matrix = mat
        return self._cache.adjusted_matrix
              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)  # type: ignore
                self._cache.adjusted_matrix = mat
        return self._cache.adjusted_matrix
                logger.trace("adjusted_matrix: %s", mat)  # type: ignore
                self._cache.adjusted_matrix = mat
        return self._cache.adjusted_matrix
                logger.trace("adjusted_matrix: %s", mat)  # type: ignore
                self._cache.adjusted_matrix = mat
        return self._cache.adjusted_matrix
  
      @property
      def face(self):
          """ :class:`numpy.ndarray`: The aligned face at the given :attr:`size` at the specified
          :attr:`coverage` in the given :attr:`dtype`. If an :attr:`image` has not been provided
keep keep keep keep replace 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