      def run(self,
              detected_face: DetectedFace,
              source_offset: np.ndarray,
              target_offset: np.ndarray,
              centering: Literal["legacy", "face", "head"],
              predicted_mask: Optional[np.ndarray] = None) -> Tuple[np.ndarray, np.ndarray]:
          """ Obtain the requested mask type and perform any defined mask manipulations.
  
          Parameters
          ----------
          detected_face: :class:`lib.align.DetectedFace`
 
</s> remove                   predicted_mask: Optional[np.ndarray],
                  centering: Literal["legacy", "face", "head"],
 </s> add                   predicted_mask: np.ndarray | None,
                  centering: T.Literal["legacy", "face", "head"], </s> remove                          centering: Literal["legacy", "face", "head"],
 </s> add                          centering: T.Literal["legacy", "face", "head"], </s> remove                         detected_face: "DetectedFace",
                        predicted_mask: Optional[np.ndarray],
                        reference_face: "AlignedFace") -> Tuple[np.ndarray, np.ndarray]:
 </s> add                         detected_face: DetectedFace,
                        predicted_mask: np.ndarray | None,
                        reference_face: AlignedFace) -> tuple[np.ndarray, np.ndarray]: </s> remove                               detected_face: "DetectedFace",
                              reference_face: "AlignedFace",
                              predicted_mask: Optional[np.ndarray]) -> np.ndarray:
 </s> add                               detected_face: DetectedFace,
                              reference_face: AlignedFace,
                              predicted_mask: np.ndarray | None) -> np.ndarray: </s> remove     def _get_face_mask(self, filename: str, detected_face: DetectedFace) -> Optional[np.ndarray]:
 </s> add     def _get_face_mask(self, filename: str, detected_face: DetectedFace) -> np.ndarray | None:
            centering: T.Literal["legacy", "face", "head"],
            predicted_mask: np.ndarray | None = None) -> tuple[np.ndarray, np.ndarray]:
      def run(self,
              detected_face: DetectedFace,
              source_offset: np.ndarray,
              target_offset: np.ndarray,
            centering: T.Literal["legacy", "face", "head"],
            predicted_mask: np.ndarray | None = None) -> tuple[np.ndarray, np.ndarray]:
            centering: T.Literal["legacy", "face", "head"],
            predicted_mask: np.ndarray | None = None) -> tuple[np.ndarray, np.ndarray]:
          """ Obtain the requested mask type and perform any defined mask manipulations.
  
          Parameters
          ----------
          detected_face: :class:`lib.align.DetectedFace`
keep keep keep keep replace replace keep keep keep keep keep
 Rebase code (#1326)

* Remove tensorflow_probability requirement

* setup.py - fix progress bars

* requirements.txt: Remove pre python 3.9 packages

* update apple requirements.txt

* update INSTALL.md

* Remove python<3.9 code

* setup.py - fix Windows Installer

* typing: python3.9 compliant

* Update pytest and readthedocs python versions

* typing fixes

* Python Version updates
  - Reduce max version to 3.10
  - Default to 3.10 in installers
  - Remove incompatible 3.11 tests

* Update dependencies

* Downgrade imageio dep for Windows

* typing: merge optional unions and fixes

* Updates
  - min python version 3.10
  - typing to python 3.10 spec
  - remove pre-tf2.10 code
  - Add conda tests

* train: re-enable optimizer saving

* Update dockerfiles

* Update setup.py
  - Apple Conda deps to setup.py
  - Better Cuda + dependency handling

* bugfix: Patch logging to prevent Autograph errors

* Update dockerfiles

* Setup.py - Setup.py - stdout to utf-8

* Add more OSes to github Actions

* suppress mac-os end to end test 
plugins/convert/mask/mask_blend.py