          self._model: Optional[Model] = None
          logger.trace("Initialized: %s", self.__class__.__name__,)  # type:ignore
  
      def predict(self,
                  feed: Union[List[np.ndarray], np.ndarray],
                  batch_size: Optional[int] = None) -> Union[List[np.ndarray], np.ndarray]:
          """ Get predictions from the model.
  
          This method is a wrapper for :func:`keras.predict()` function. For Tensorflow backends
          this is a straight call to the predict function.
  
 
</s> remove         self._model: Optional[Model] = None
 </s> add         self._model: Model | None = None </s> remove     def _predict(self, feed_faces: np.ndarray, batch_size: T.Optional[int] = None) -> np.ndarray:
 </s> add     def _predict(self, feed_faces: np.ndarray, batch_size: int | None = None) -> np.ndarray: </s> remove         self._normalize_method = cast(Optional[Literal["clahe", "hist", "mean"]], method)
 </s> add         self._normalize_method = T.cast(T.Literal["clahe", "hist", "mean"] | None, method) </s> remove         batch.feed = np.array([cast(np.ndarray, feed.face)[..., :3]
 </s> add         batch.feed = np.array([T.cast(np.ndarray, feed.face)[..., :3] </s> remove         faces: List["AlignedFace"] = feed[1]
 </s> add         faces: list[AlignedFace] = feed[1]
                feed: list[np.ndarray] | np.ndarray,
                batch_size: int | None = None) -> list[np.ndarray] | np.ndarray:
          self._model: Optional[Model] = None
          logger.trace("Initialized: %s", self.__class__.__name__,)  # type:ignore
  
      def predict(self,
                feed: list[np.ndarray] | np.ndarray,
                batch_size: int | None = None) -> list[np.ndarray] | np.ndarray:
                feed: list[np.ndarray] | np.ndarray,
                batch_size: int | None = None) -> list[np.ndarray] | np.ndarray:
          """ Get predictions from the model.
  
          This method is a wrapper for :func:`keras.predict()` function. For Tensorflow backends
          this is a straight call to the predict function.
  
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 
lib/model/session.py