          The scaling to apply to the pool
      crop: tuple
          The amount of 2D cropping to apply. Tuple of `ints`
      """
      def __init__(self, level: int, scale: float, crop: Tuple[int, int]):
          self._name = f"_pool{level}"
          self._cropping = (crop, crop)
          self._scale = scale
  
      def __call__(self, inputs: Tensor) -> Tensor:
 
</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         norms = dict(batch=BatchNormalization,
                     group=GroupNormalization,
                     instance=InstanceNormalization,
                     layer=LayerNormalization,
                     rms=RMSNormalization)
 </s> add         norms = {"batch": BatchNormalization,
                 "group": GroupNormalization,
                 "instance": InstanceNormalization,
                 "layer": LayerNormalization,
                 "rms": RMSNormalization} </s> remove     def __init__(self, input_shape: Tuple[int, ...], config: dict) -> None:
 </s> add     def __init__(self, input_shape: T.Tuple[int, ...], config: dict) -> None: </s> remove                  model_path: List[str],
 </s> add                  model_path: T.List[str], </s> remove                  model: "ModelBase",
 </s> add                  model: ModelBase,
    def __init__(self, level: int, scale: float, crop: T.Tuple[int, int]):
          The scaling to apply to the pool
      crop: tuple
          The amount of 2D cropping to apply. Tuple of `ints`
      """
    def __init__(self, level: int, scale: float, crop: T.Tuple[int, int]):
          self._name = f"_pool{level}"
          self._cropping = (crop, crop)
          self._scale = scale
  
      def __call__(self, inputs: Tensor) -> Tensor:
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/mask/vgg_clear.py