  import numpy as np
  import keras  # pylint:disable=import-error
  import keras.backend as K  # pylint:disable=import-error
  
  from lib.model.session import KSession
  from ._base import Detector, logger
  
  
 
</s> remove         """ Detect faces """
 </s> add         """ Process the output from the model to obtain faces

        Parameters
        ----------
        bounding_boxes_scales: list
            The output predictions from the S3FD model
        """ </s> remove         tuple
            An output shape tuple.
 </s> add         tensor
            The output tensor from the convolution block </s> remove     def call(self, inputs, **kwargs):  # pylint:disable=unused-argument
        """This is where the layer's logic lives.
 </s> add         var_x = self.conv_block(var_x, 256, 3, 3)
        f3_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x) </s> remove         dict
            The configuration for the layer
 </s> add         tensor
            The output tensor from the convolution block </s> remove         tuple
            An output shape tuple.
 </s> add         tensor:
            The output from the L2 Normalization Layer
from keras.layers import Concatenate, Conv2D, Input, Maximum, MaxPooling2D, ZeroPadding2D
  import numpy as np
  import keras  # pylint:disable=import-error
  import keras.backend as K  # pylint:disable=import-error
from keras.layers import Concatenate, Conv2D, Input, Maximum, MaxPooling2D, ZeroPadding2D
  
  from lib.model.session import KSession
  from ._base import Detector, logger
  
  
keep keep add keep keep keep keep keep
 extract: S3FD - Convert to re-enable CPU 
plugins/extract/detect/s3fd.py