              logger.warning("Swallowed OS Error caused by Tensorflow distributed training. output "
                             "line: %s, error: %s", output, str(err))
  
      def _update_viewers(self,
                          viewer: Optional[Callable[[np.ndarray, str], None]],
                          timelapse_kwargs: Optional[Dict[Literal["input_a",
                                                                  "input_b",
                                                                  "output"], str]]) -> None:
          """ Update the preview viewer and timelapse output
  
          Parameters
          ----------
          viewer: :func:`scripts.train.Train._show` or ``None``
 
</s> remove                        viewer: Optional[Callable[[np.ndarray, str], None]],
                       timelapse_kwargs: Optional[Dict[Literal["input_a",
                                                               "input_b",
                                                               "output"], str]]) -> None:
 </s> add                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                       timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                   "input_b",
                                                                   "output"], str]]) -> None: </s> remove     def output_timelapse(self, timelapse_kwargs: Dict[Literal["input_a",
                                                              "input_b",
                                                              "output"], str]) -> None:
 </s> add     def output_timelapse(self, timelapse_kwargs: T.Dict[Literal["input_a",
                                                                "input_b",
                                                                "output"], str]) -> None: </s> remove             raise FaceswapError("Config error: output_size must be one of: 128, 256, or 384.")
 </s> add             raise FaceswapError("Config error: output_size must be one of: "
                                "128, 256, or 384.") from err </s> remove         except KeyError:
 </s> add         except KeyError as err: </s> remove     def generate_preview(self,
                         is_timelapse: bool = False) -> Dict[Literal["a", "b"], List[np.ndarray]]:
 </s> add     def generate_preview(self, is_timelapse: bool = False
                         ) -> T.Dict[Literal["a", "b"], T.List[np.ndarray]]:
                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                        timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                    "input_b",
                                                                    "output"], str]]) -> None:
              logger.warning("Swallowed OS Error caused by Tensorflow distributed training. output "
                             "line: %s, error: %s", output, str(err))
  
      def _update_viewers(self,
                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                        timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                    "input_b",
                                                                    "output"], str]]) -> None:
                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                        timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                    "input_b",
                                                                    "output"], str]]) -> None:
                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                        timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                    "input_b",
                                                                    "output"], str]]) -> None:
                        viewer: T.Optional[T.Callable[[np.ndarray, str], None]],
                        timelapse_kwargs: T.Optional[T.Dict[Literal["input_a",
                                                                    "input_b",
                                                                    "output"], str]]) -> None:
          """ Update the preview viewer and timelapse output
  
          Parameters
          ----------
          viewer: :func:`scripts.train.Train._show` or ``None``
keep keep keep keep replace replace 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