          self._input_size = input_size
          self._threshold = threshold
  
      @staticmethod
      def model_definition() -> Tuple[List[Tensor], List[Tensor]]:
          """ Keras O-Network for MTCNN """
          input_ = Input(shape=(48, 48, 3))
          var_x = Conv2D(32, (3, 3), strides=1, padding='valid', name='conv1')(input_)
          var_x = PReLU(shared_axes=[1, 2], name='prelu1')(var_x)
          var_x = MaxPool2D(pool_size=3, strides=2, padding='same')(var_x)
 
</s> remove         self._pnet_input: Optional[List[np.ndarray]] = None
 </s> add         self._pnet_input: T.Optional[T.List[np.ndarray]] = None </s> remove     def model_definition(self) -> Tuple[List[Tensor], List[Tensor]]:
 </s> add     def model_definition(self) -> T.Tuple[T.List[Tensor], T.List[Tensor]]: </s> remove             var_x = MaxPool2D(pool_size=3, strides=2, name=f"{name}.pool")(var_x)
        var_x = ZeroPadding2D(padding=padding, name=f"{name}.pad")(var_x)
        var_x = Conv2D(filters,
                       kernel_size=kernel_size,
                       strides=strides,
                       padding="valid",
                       activation="relu",
                       name=name)(var_x)
 </s> add             var_x = layers.MaxPool2D(pool_size=3, strides=2, name=f"{name}.pool")(var_x)
        var_x = layers.ZeroPadding2D(padding=padding, name=f"{name}.pad")(var_x)
        var_x = layers.Conv2D(filters,
                              kernel_size=kernel_size,
                              strides=strides,
                              padding="valid",
                              activation="relu",
                              name=name)(var_x) </s> remove         return KerasModel(input_, var_x, name="encoder")
 </s> add         return KModel(input_, var_x, name="encoder")
 </s> remove         return KerasModel(input_, var_x, name="encoder")
 </s> add         return KModel(input_, var_x, name="encoder")
    def model_definition() -> T.Tuple[T.List[Tensor], T.List[Tensor]]:
          self._input_size = input_size
          self._threshold = threshold
  
      @staticmethod
    def model_definition() -> T.Tuple[T.List[Tensor], T.List[Tensor]]:
          """ Keras O-Network for MTCNN """
          input_ = Input(shape=(48, 48, 3))
          var_x = Conv2D(32, (3, 3), strides=1, padding='valid', name='conv1')(input_)
          var_x = PReLU(shared_axes=[1, 2], name='prelu1')(var_x)
          var_x = MaxPool2D(pool_size=3, strides=2, padding='same')(var_x)
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/mtcnn.py