          assert isinstance(num_images, int)
          self._timelapse = _Timelapse(self._model,
                                       self._model.coverage_ratio,
                                       num_images,
                                       cast(int, self._config["mask_opacity"]),
                                       cast(str, self._config["mask_color"]),
                                       self._feeder,
                                       self._images)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def _get_config(self, configfile: Optional[str]) -> Dict[str, "ConfigValueType"]:
 
</s> remove                                  cast(int, self._config["mask_opacity"]),
                                 cast(str, self._config["mask_color"]))
 </s> add                                  T.cast(int, self._config["mask_opacity"]),
                                 T.cast(str, self._config["mask_color"])) </s> remove     def _get_config(self, configfile: Optional[str]) -> Dict[str, "ConfigValueType"]:
 </s> add     def _get_config(self, configfile: T.Optional[str]) -> T.Dict[str, ConfigValueType]: </s> remove                 configfile: Optional[str] = None) -> Dict[str, "ConfigValueType"]:
 </s> add                 configfile: T.Optional[str] = None) -> T.Dict[str, ConfigValueType]: </s> remove         retval: Dict[Literal["a", "b"], List[np.ndarray]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.List[np.ndarray]] = {} </s> remove                  configfile: Optional[str]) -> None:
 </s> add                  configfile: T.Optional[str]) -> None:
                                     T.cast(int, self._config["mask_opacity"]),
                                     T.cast(str, self._config["mask_color"]),
          assert isinstance(num_images, int)
          self._timelapse = _Timelapse(self._model,
                                       self._model.coverage_ratio,
                                       num_images,
                                     T.cast(int, self._config["mask_opacity"]),
                                     T.cast(str, self._config["mask_color"]),
                                     T.cast(int, self._config["mask_opacity"]),
                                     T.cast(str, self._config["mask_color"]),
                                       self._feeder,
                                       self._images)
          logger.debug("Initialized %s", self.__class__.__name__)
  
      def _get_config(self, configfile: Optional[str]) -> Dict[str, "ConfigValueType"]:
keep keep keep keep replace 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