          pre_face_count = self._alignments.faces_count
          self._alignments.filter_faces(accept_dict, filter_out=False)
          logger.info("Faces filtered out: %s", pre_face_count - self._alignments.faces_count)
  
      def _get_face_metadata(self) -> Dict[str, List[int]]:
          """ Check for the existence of an aligned directory for identifying which faces in the
          target frames should be swapped. If it exists, scan the folder for face's metadata
  
          Returns
          -------
 
</s> remove         retval: Dict[str, List[int]] = {}
 </s> add         retval: T.Dict[str, T.List[int]] = {} </s> remove             The output of this function must be a keras model generated from
            :class:`plugins.train.model._base.KerasModel`. See Keras documentation for the correct
 </s> add             See Keras documentation for the correct
 </s> remove             The output of this function must be a keras model generated from
            :class:`plugins.train.model._base.KerasModel`. See Keras documentation for the correct
            structure, but note that parameter :attr:`name` is a required rather than an optional
            argument in Faceswap. You should assign this to the attribute ``self.name`` that is
            automatically generated from the plugin's filename.
 </s> add             The generated model </s> remove                       faces: List[DetectedFace],
                      sub_folders: List[Optional[str]],
                      should_filter: List[bool]) -> List[DetectedFace]:
 </s> add                       faces: T.List[DetectedFace],
                      sub_folders: T.List[T.Optional[str]],
                      should_filter: T.List[bool]) -> T.List[DetectedFace]: </s> remove     def _get_detected_faces(self, filename: str, image: np.ndarray) -> List[DetectedFace]:
 </s> add     def _get_detected_faces(self, filename: str, image: np.ndarray) -> T.List[DetectedFace]:
    def _get_face_metadata(self) -> T.Dict[str, T.List[int]]:
          pre_face_count = self._alignments.faces_count
          self._alignments.filter_faces(accept_dict, filter_out=False)
          logger.info("Faces filtered out: %s", pre_face_count - self._alignments.faces_count)
  
    def _get_face_metadata(self) -> T.Dict[str, T.List[int]]:
          """ Check for the existence of an aligned directory for identifying which faces in the
          target frames should be swapped. If it exists, scan the folder for face's metadata
  
          Returns
          -------
keep keep keep keep replace keep keep keep keep keep
 Remove plaidML support (#1325)

* Remove PlaidML reference from readme files

* Remove AMD option from installers

* remove amd requirements and update setup.py

* remove plaidml test from CI workflow

* gpustats: remove plaidml backend

* plaid removals:
  - faceswap.py - python version check
  - setup.cfg - plaidml typing ignore
  - lib.keras_utils - All plaid code
  - lib.launcher.py - All plaidml checks and configuration

* remove tf2.2 specific code from GUI event reader

* lib.model - remove all plaidml implementations

* plugins.extract - remove plaidml code

* plugins.train remove plaidml code

* lib.convert - remove plaidml code

* tools.model: remove plaidml code

* Remove plaidML tests from unit tests

* remove plaidml_utils and docsting cleanups

* Remove plaidML refs from configs

* fix keras imports 
scripts/convert.py