          return header_box
  
      @classmethod
      def _duplicate_headers(cls,
                             headers: Dict[Literal["a", "b"], np.ndarray],
                             columns: int) -> Dict[Literal["a", "b"], np.ndarray]:
          """ Duplicate headers for the number of columns displayed for each side.
  
          Parameters
          ----------
          headers: dict
 
</s> remove                        feed: Dict[Literal["a", "b"], np.ndarray],
                       samples: Dict[Literal["a", "b"], np.ndarray],
                       masks: Dict[Literal["a", "b"], np.ndarray]
                       ) -> Dict[Literal["a", "b"], List[np.ndarray]]:
 </s> add                        feed: T.Dict[Literal["a", "b"], np.ndarray],
                       samples: T.Dict[Literal["a", "b"], np.ndarray],
                       masks: T.Dict[Literal["a", "b"], np.ndarray]
                       ) -> T.Dict[Literal["a", "b"], T.List[np.ndarray]]: </s> remove         figures: Dict[Literal["a", "b"], np.ndarray] = {}
        headers: Dict[Literal["a", "b"], np.ndarray] = {}
 </s> add         figures: T.Dict[Literal["a", "b"], np.ndarray] = {}
        headers: T.Dict[Literal["a", "b"], np.ndarray] = {} </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]]: </s> remove         retval: Dict[Literal["a", "b"], Generator[BatchType, None, None]] = {}
 </s> add         retval: T.Dict[Literal["a", "b"], T.Generator[BatchType, None, None]] = {} </s> remove                            images: Dict[Literal["a", "b"], List[str]],
 </s> add                            images: T.Dict[Literal["a", "b"], T.List[str]],
                           headers: T.Dict[Literal["a", "b"], np.ndarray],
                           columns: int) -> T.Dict[Literal["a", "b"], np.ndarray]:
          return header_box
  
      @classmethod
      def _duplicate_headers(cls,
                           headers: T.Dict[Literal["a", "b"], np.ndarray],
                           columns: int) -> T.Dict[Literal["a", "b"], np.ndarray]:
                           headers: T.Dict[Literal["a", "b"], np.ndarray],
                           columns: int) -> T.Dict[Literal["a", "b"], np.ndarray]:
          """ Duplicate headers for the number of columns displayed for each side.
  
          Parameters
          ----------
          headers: dict
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