      def __init__(self,
                   model: "ModelBase",
                   images: Dict[Literal["a", "b"], List[str]],
                   batch_size: int,
                   configfile: Optional[str]) -> None:
          logger.debug("Initializing %s: (model: '%s', batch_size: %s)",
                       self.__class__.__name__, model, batch_size)
          self._model = model
          self._config = self._get_config(configfile)
  
 
</s> remove                  model: "ModelBase",
                 images: Dict[Literal["a", "b"], List[str]],
 </s> add                  model: ModelBase,
                 images: T.Dict[Literal["a", "b"], T.List[str]], </s> remove                  config: Dict[str, "ConfigValueType"]) -> None:
 </s> add                  config: T.Dict[str, ConfigValueType]) -> None: </s> remove                  images: Dict[Literal["a", "b"], List[str]],
                 model: 'ModelBase',
 </s> add                  images: T.Dict[Literal["a", "b"], T.List[str]],
                 model: ModelBase, </s> remove                  image_paths: Dict[Literal["a", "b"], List[str]]) -> None:
 </s> add                  image_paths: T.Dict[Literal["a", "b"], T.List[str]]) -> None: </s> remove         iterator = cast(Dict[Literal["a", "b"], Generator[BatchType, None, None]],
                        self._display_feeds["timelapse"])
 </s> add         iterator = T.cast(T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]],
                          self._display_feeds["timelapse"])
                 configfile: T.Optional[str]) -> None:
      def __init__(self,
                   model: "ModelBase",
                   images: Dict[Literal["a", "b"], List[str]],
                   batch_size: int,
                 configfile: T.Optional[str]) -> None:
          logger.debug("Initializing %s: (model: '%s', batch_size: %s)",
                       self.__class__.__name__, model, batch_size)
          self._model = model
          self._config = self._get_config(configfile)
  
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