          The scaling to apply to the pool
      crop: tuple
          The amount of 2D cropping to apply. Tuple of `ints`
      """
      def __init__(self, level: int, scale: float, crop: T.Tuple[int, int]):
          self._name = f"_pool{level}"
          self._cropping = (crop, crop)
          self._scale = scale
  
      def __call__(self, inputs: Tensor) -> Tensor:
 
</s> remove                  kernel_size: T.Union[int, T.Tuple[int, int]] = 3,
 </s> add                  kernel_size: int | tuple[int, int] = 3, </s> remove     detected_faces: List[List["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: List[np.ndarray] = field(default_factory=list)
    scale: List[float] = field(default_factory=list)
    pad: List[Tuple[int, int]] = field(default_factory=list)
 </s> add     detected_faces: list[list["DetectedFace"]] = field(default_factory=list)
    rotation_matrix: list[np.ndarray] = field(default_factory=list)
    scale: list[float] = field(default_factory=list)
    pad: list[tuple[int, int]] = field(default_factory=list) </s> remove                mode: Literal["full", "cap_max", "cap_min"] = "full") -> T.List[int]:
 </s> add                mode: T.Literal["full", "cap_max", "cap_min"] = "full") -> list[int]: </s> remove                  kernel_size: T.Union[int, T.Tuple[int, int]] = 5,
                 strides: T.Union[int, T.Tuple[int, int]] = 2, **kwargs) -> None:
 </s> add                  kernel_size: int | tuple[int, int] = 5,
                 strides: int | tuple[int, int] = 2, **kwargs) -> None: </s> remove     def __init__(self, input_shape: T.Tuple[int, ...], config: dict) -> None:
 </s> add     def __init__(self, input_shape: tuple[int, ...], config: dict) -> None:
    def __init__(self, level: int, scale: float, crop: tuple[int, int]):
          The scaling to apply to the pool
      crop: tuple
          The amount of 2D cropping to apply. Tuple of `ints`
      """
    def __init__(self, level: int, scale: float, crop: tuple[int, int]):
          self._name = f"_pool{level}"
          self._cropping = (crop, crop)
          self._scale = scale
  
      def __call__(self, inputs: Tensor) -> Tensor:
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 
plugins/extract/mask/vgg_clear.py