          self._blur_passes: int = 0
          self._blur_kernel: Union[float, int] = 0
          self._threshold = 0.0
          self._sub_crop_size = 0
          self._sub_crop_slices: Dict[Literal["in", "out"], List[slice]] = {}
  
          self.set_blur_and_threshold()
          logger.trace("Initialized: %s", self.__class__.__name__)  # type: ignore
  
      @property
 
</s> remove         self._stats: Dict[str, np.ndarray] = {}
 </s> add         self._stats: dict[str, np.ndarray] = {} </s> remove         self._bins: Dict[int, int] = {}
 </s> add         self._bins: dict[int, int] = {} </s> remove     adjusted_matrix: Optional[np.ndarray] = None
    interpolators: Tuple[int, int] = (0, 0)
    cropped_roi: Dict[CenteringType, np.ndarray] = field(default_factory=dict)
    cropped_slices: Dict[CenteringType, Dict[Literal["in", "out"],
                                             Tuple[slice, slice]]] = field(default_factory=dict)
 </s> add     adjusted_matrix: np.ndarray | None = None
    interpolators: tuple[int, int] = (0, 0)
    cropped_roi: dict[CenteringType, np.ndarray] = field(default_factory=dict)
    cropped_slices: dict[CenteringType, dict[T.Literal["in", "out"],
                                             tuple[slice, slice]]] = field(default_factory=dict) </s> remove         self._args: Dict[str, Union[int, float]] = {"avg_samples": avg_samples,
                                                    "smooth_amount": smooth_amount,
                                                    "flatten_outliers": flatten_outliers}
 </s> add         self._args: dict[str, int | float] = {"avg_samples": avg_samples,
                                              "smooth_amount": smooth_amount,
                                              "flatten_outliers": flatten_outliers} </s> remove         seen: Dict[str, List[int]] = {}
 </s> add         seen: dict[str, list[int]] = {}
        self._sub_crop_slices: dict[T.Literal["in", "out"], list[slice]] = {}
          self._blur_passes: int = 0
          self._blur_kernel: Union[float, int] = 0
          self._threshold = 0.0
          self._sub_crop_size = 0
        self._sub_crop_slices: dict[T.Literal["in", "out"], list[slice]] = {}
  
          self.set_blur_and_threshold()
          logger.trace("Initialized: %s", self.__class__.__name__)  # type: ignore
  
      @property
keep keep keep keep 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 
lib/align/detected_face.py