          self._config = config
          self._feeds = {side: self._load_generator(side, False).minibatch_ab()
                         for side in get_args(Literal["a", "b"])}
  
          self._display_feeds = dict(preview=self._set_preview_feed(), timelapse={})
          logger.debug("Initialized %s:", self.__class__.__name__)
  
      def _load_generator(self,
                          side: Literal["a", "b"],
                          is_display: bool,
 
</s> remove                         batch_size: Optional[int] = None,
                        images: Optional[List[str]] = None) -> DataGenerator:
 </s> add                         batch_size: T.Optional[int] = None,
                        images: T.Optional[T.List[str]] = None) -> DataGenerator: </s> remove                  layer_indicies: Optional[Tuple[int, int]] = None) -> None:
 </s> add                  layer_indicies: T.Optional[T.Tuple[int, int]] = None) -> None: </s> remove                  input_shapes: Union[list, tuple],
 </s> add                  input_shapes: T.Union[list, tuple], </s> remove         retval: Dict[Literal["a", "b"], List[np.ndarray]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.List[np.ndarray]] = {} </s> remove         retval: Dict[Literal["a", "b"], Generator[BatchType, None, None]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]] = {}
        self._display_feeds = {"preview": self._set_preview_feed(), "timelapse": {}}
          self._config = config
          self._feeds = {side: self._load_generator(side, False).minibatch_ab()
                         for side in get_args(Literal["a", "b"])}
  
        self._display_feeds = {"preview": self._set_preview_feed(), "timelapse": {}}
          logger.debug("Initialized %s:", self.__class__.__name__)
  
      def _load_generator(self,
                          side: Literal["a", "b"],
                          is_display: bool,
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 
plugins/train/trainer/_base.py