                           for _ in range(self._batch_size)]
              retval = self._process_batch(img_paths)
              yield retval
  
      def _get_images_with_meta(self, filenames: List[str]) -> Tuple[np.ndarray, List[DetectedFace]]:
          """ Obtain the raw face images with associated :class:`DetectedFace` objects for this
          batch.
  
          If this is the first time a face has been loaded, then it's meta data is extracted
          from the png header and added to :attr:`_face_cache`.
 
</s> remove     def _process_batch(self, filenames: List[str]) -> BatchType:
 </s> add     def _process_batch(self, filenames: list[str]) -> BatchType: </s> remove                          ) -> Dict[str, Dict[str, "AlignmentDict"]]:
 </s> add                          ) -> dict[str, dict[str, AlignmentDict]]: </s> remove     def update_png_header(self, filename: str, alignments: "PNGHeaderAlignmentsDict") -> None:
 </s> add     def update_png_header(self, filename: str, alignments: PNGHeaderAlignmentsDict) -> None: </s> remove     def get_items(self, filenames: List[str]) -> List[DetectedFace]:
 </s> add     def get_items(self, filenames: list[str]) -> list[DetectedFace]: </s> remove     def _identity_from_extracted(cls, filename) -> Tuple[np.ndarray, bool]:
 </s> add     def _identity_from_extracted(cls, filename) -> tuple[np.ndarray, bool]:
    def _get_images_with_meta(self, filenames: list[str]) -> tuple[np.ndarray, list[DetectedFace]]:
                           for _ in range(self._batch_size)]
              retval = self._process_batch(img_paths)
              yield retval
  
    def _get_images_with_meta(self, filenames: list[str]) -> tuple[np.ndarray, list[DetectedFace]]:
          """ Obtain the raw face images with associated :class:`DetectedFace` objects for this
          batch.
  
          If this is the first time a face has been loaded, then it's meta data is extracted
          from the png header and added to :attr:`_face_cache`.
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/training/generator.py