          if not self._filter_files and not self._nfilter_files:
              logger.debug("Filter not selected. Exiting %s", self.__class__.__name__)
              return
  
          self._embeddings: List[np.ndarray] = [np.array([]) for _ in self._filter_files]
          self._nembeddings: List[np.ndarray] = [np.array([]) for _ in self._nfilter_files]
          self._extractor = extractor
  
          self._get_embeddings()
          self._extractor.recognition.add_identity_filters(self.embeddings,
                                                           self.n_embeddings,
 
</s> remove         found_faces: List[np.ndarray] = [np.array([]) for _ in range(len(batch.feed))]
 </s> add         found_faces: list[np.ndarray] = [np.array([]) for _ in range(len(batch.feed))] </s> remove             retval = dict(faces_dir=faces,
                          frames_dir=[None for _ in range(len(faces))],
                          alignments_file=[None for _ in range(len(faces))])
 </s> add             retval = {"faces_dir": faces,
                      "frames_dir": [None for _ in range(len(faces))],
                      "alignments_file": [None for _ in range(len(faces))]} </s> remove         retval: List[np.ndarray] = []
        filtered_landmarks: List[np.ndarray] = []
 </s> add         retval: list[np.ndarray] = []
        filtered_landmarks: list[np.ndarray] = [] </s> remove             faces: list[Optional[str]] = [None for _ in range(len(frames))]
 </s> add             faces: list[str | None] = [None for _ in range(len(frames))] </s> remove         sub_folders: List[Optional[str]] = [None for _ in range(len(faces))]
 </s> add         sub_folders: list[str | None] = [None for _ in range(len(faces))]
        self._embeddings: list[np.ndarray] = [np.array([]) for _ in self._filter_files]
        self._nembeddings: list[np.ndarray] = [np.array([]) for _ in self._nfilter_files]
          if not self._filter_files and not self._nfilter_files:
              logger.debug("Filter not selected. Exiting %s", self.__class__.__name__)
              return
  
        self._embeddings: list[np.ndarray] = [np.array([]) for _ in self._filter_files]
        self._nembeddings: list[np.ndarray] = [np.array([]) for _ in self._nfilter_files]
        self._embeddings: list[np.ndarray] = [np.array([]) for _ in self._filter_files]
        self._nembeddings: list[np.ndarray] = [np.array([]) for _ in self._nfilter_files]
          self._extractor = extractor
  
          self._get_embeddings()
          self._extractor.recognition.add_identity_filters(self.embeddings,
                                                           self.n_embeddings,
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 
scripts/extract.py