          self.load_model_weights()
  
      @staticmethod
      def model_definition():
          """ Keras P-Network for MTCNN """
          input_ = Input(shape=(None, None, 3))
          var_x = Conv2D(10, (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=2)(var_x)
          var_x = Conv2D(16, (3, 3), strides=1, padding='valid', name='conv2')(var_x)
 
</s> remove         """ Keras R-Network for MTCNN """
 </s> add         """ Keras R-Network Definition for MTCNN """ </s> remove     """ MTCNN detector for face recognition """
    def __init__(self, **kwargs):
 </s> add     """ MTCNN detector for face recognition. """
    def __init__(self, **kwargs) -> None: </s> remove     def validate_kwargs(self):
 </s> add     def _validate_kwargs(self) -> Dict[str, Union[int, float, List[float]]]:
        """ Keras P-Network Definition for MTCNN """
          self.load_model_weights()
  
      @staticmethod
      def model_definition():
        """ Keras P-Network Definition for MTCNN """
          input_ = Input(shape=(None, None, 3))
          var_x = Conv2D(10, (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=2)(var_x)
          var_x = Conv2D(16, (3, 3), strides=1, padding='valid', name='conv2')(var_x)
keep keep keep keep replace keep keep keep keep keep
 Add CPU option to BiSeNet and MTCNN
  - Add CPU option to KSession
  - MTCNN optimizations
  - Update docs for bisenet + mtcnn 
plugins/extract/detect/mtcnn.py