          self._axes = axes
          self._steps = steps
          super().__init__(**kwargs)
  
      def _get_slices(self, dimensions: int) -> List[Tuple[int, ...]]:
          """ Obtain slices for the given number of dimensions.
  
          Parameters
          ----------
          dimensions: int
 
</s> remove                  starts: List[int],
                 ends: List[int],
                 axes: Optional[List[int]] = None,
                 steps: Optional[List[int]] = None,
 </s> add                  starts: T.List[int],
                 ends: T.List[int],
                 axes: T.Optional[T.List[int]] = None,
                 steps: T.Optional[T.List[int]] = None, </s> remove                mode: Literal["full", "cap_max", "cap_min"] = "full") -> List[int]:
 </s> add                mode: Literal["full", "cap_max", "cap_min"] = "full") -> T.List[int]: </s> remove         inputs: :class:`plaidml.tile.Value` or :class:`tf.Tensor`
 </s> add         inputs: :class:`tf.Tensor` </s> remove                            headers: Dict[Literal["a", "b"], np.ndarray],
                           columns: int) -> Dict[Literal["a", "b"], np.ndarray]:
 </s> add                            headers: T.Dict[Literal["a", "b"], np.ndarray],
                           columns: int) -> T.Dict[Literal["a", "b"], np.ndarray]: </s> remove     def compute_output_shape(self, input_shape: Tuple[int, ...]) -> Tuple[int, ...]:
 </s> add     def compute_output_shape(self, input_shape: T.Tuple[int, ...]) -> T.Tuple[int, ...]:
    def _get_slices(self, dimensions: int) -> T.List[T.Tuple[int, ...]]:
          self._axes = axes
          self._steps = steps
          super().__init__(**kwargs)
  
    def _get_slices(self, dimensions: int) -> T.List[T.Tuple[int, ...]]:
          """ Obtain slices for the given number of dimensions.
  
          Parameters
          ----------
          dimensions: int
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/extract/detect/s3fd.py