          self.load_model_weights()
  
      @staticmethod
      def model_definition():
          """ Keras R-Network for MTCNN """
          input_ = Input(shape=(24, 24, 3))
          var_x = Conv2D(28, (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         """ Keras P-Network for MTCNN """
 </s> add         """ Keras P-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                          exclude_gpus=exclude_gpus)
 </s> add                          exclude_gpus=exclude_gpus,
                         cpu_mode=cpu_mode)
        """ Keras R-Network Definition for MTCNN """
          self.load_model_weights()
  
      @staticmethod
      def model_definition():
        """ Keras R-Network Definition for MTCNN """
          input_ = Input(shape=(24, 24, 3))
          var_x = Conv2D(28, (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
 Add CPU option to BiSeNet and MTCNN
  - Add CPU option to KSession
  - MTCNN optimizations
  - Update docs for bisenet + mtcnn 
plugins/extract/detect/mtcnn.py