              Randomly selected closest matches from the other side's landmarks
          """
          logger.trace("Retrieving closest matched landmarks: (filenames: '%s', "  # type: ignore
                       "src_points: '%s')", filenames, batch_src_points)
          lm_side: Literal["a", "b"] = "a" if self._side == "b" else "b"
          other_cache = get_cache(lm_side)
          landmarks = other_cache.aligned_landmarks
  
          try:
              closest_matches = [self._nearest_landmarks[os.path.basename(filename)]
 
</s> remove         figures: T.Dict[Literal["a", "b"], np.ndarray] = {}
        headers: T.Dict[Literal["a", "b"], np.ndarray] = {}
 </s> add         figures: dict[T.Literal["a", "b"], np.ndarray] = {}
        headers: dict[T.Literal["a", "b"], np.ndarray] = {} </s> remove         batch_closest_matches: List[Tuple[str, ...]] = []
 </s> add         batch_closest_matches: list[tuple[str, ...]] = [] </s> remove     def _get_closest_match(self, filenames: List[str], batch_src_points: np.ndarray) -> np.ndarray:
 </s> add     def _get_closest_match(self, filenames: list[str], batch_src_points: np.ndarray) -> np.ndarray: </s> remove     def pre_fill(self, filenames: List[str], side: Literal["a", "b"]) -> None:
 </s> add     def pre_fill(self, filenames: list[str], side: T.Literal["a", "b"]) -> None: </s> remove         faces: List[AlignedFace] = batch.data[0]["aligned_faces"]
 </s> add         faces: list[AlignedFace] = batch.data[0]["aligned_faces"]
        lm_side: T.Literal["a", "b"] = "a" if self._side == "b" else "b"
              Randomly selected closest matches from the other side's landmarks
          """
          logger.trace("Retrieving closest matched landmarks: (filenames: '%s', "  # type: ignore
                       "src_points: '%s')", filenames, batch_src_points)
        lm_side: T.Literal["a", "b"] = "a" if self._side == "b" else "b"
          other_cache = get_cache(lm_side)
          landmarks = other_cache.aligned_landmarks
  
          try:
              closest_matches = [self._nearest_landmarks[os.path.basename(filename)]
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