              cv2.rectangle(img, (t_l, b_r), (t_l + length, b_r - length), color, 1)
          logger.debug("Overlayed background. Shape: %s", images.shape)
          return images
  
      def _compile_masked(self, faces: List[np.ndarray], masks: np.ndarray) -> List[np.ndarray]:
          """ Add the mask to the faces for masked preview.
  
          Places an opaque red layer over areas of the face that are masked out.
  
          Parameters
 
</s> remove         masks3: Union[List[np.ndarray], np.ndarray] = []
 </s> add         masks3: T.Union[T.List[np.ndarray], np.ndarray] = [] </s> remove                       color: Tuple[float, float, float]) -> np.ndarray:
 </s> add                       color: T.Tuple[float, float, float]) -> np.ndarray: </s> remove                        samples: List[np.ndarray],
                       predictions: List[np.ndarray]) -> List[np.ndarray]:
 </s> add                        samples: T.List[np.ndarray],
                       predictions: T.List[np.ndarray]) -> T.List[np.ndarray]: </s> remove                       faces: List[DetectedFace],
                      sub_folders: List[Optional[str]],
                      should_filter: List[bool]) -> List[DetectedFace]:
 </s> add                       faces: T.List[DetectedFace],
                      sub_folders: T.List[T.Optional[str]],
                      should_filter: T.List[bool]) -> T.List[DetectedFace]: </s> remove     def _get_detected_faces(self, filename: str, image: np.ndarray) -> List[DetectedFace]:
 </s> add     def _get_detected_faces(self, filename: str, image: np.ndarray) -> T.List[DetectedFace]:
    def _compile_masked(self, faces: T.List[np.ndarray], masks: np.ndarray) -> T.List[np.ndarray]:
              cv2.rectangle(img, (t_l, b_r), (t_l + length, b_r - length), color, 1)
          logger.debug("Overlayed background. Shape: %s", images.shape)
          return images
  
    def _compile_masked(self, faces: T.List[np.ndarray], masks: np.ndarray) -> T.List[np.ndarray]:
          """ Add the mask to the faces for masked preview.
  
          Places an opaque red layer over areas of the face that are masked out.
  
          Parameters
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