          **kwargs: Additional keyword arguments.
              Required for parent class but unused
          Returns
          -------
          A tensor or list/tuple of tensors.
              The layer output
          """
          return inputs[0] / inputs[1]
  
  
  class S3fd(KSession):
 
</s> remove         A tensor or list/tuple of tensors.
            The layer output
 </s> add         dict
            The configuration for the layer </s> remove         inputs: Input tensor, or list/tuple of input tensors.
            The input to the layer
        **kwargs: Additional keyword arguments.
            Required for parent class but unused
 </s> add         batch: class:`numpy.ndarray`
            The batch to be fed to the model
 </s> remove         Parameters
        ----------
        inputs: Input tensor, or list/tuple of input tensors.
            The input to the layer
        **kwargs: Additional keyword arguments.
            Required for parent class but unused
 </s> add  </s> remove         Parameters
        ----------
        inputs: Input tensor, or list/tuple of input tensors.
            The input to the layer. Required for parent class but unused
        **kwargs: Additional keyword arguments.
            Required for parent class but unused
        Returns
        -------
        A tensor or list/tuple of tensors.
            The layer output
        """
        data = K.constant(self._constant, dtype=self._dtype)
        return data
 </s> add         bmax = Maximum()([chunks[0], chunks[1], chunks[2]])
        cls1 = Concatenate()([bmax, chunks[3]]) </s> remove         Parameters
        ----------
        inputs: Input tensor, or list/tuple of input tensors.
            The input to the layer
        **kwargs: Additional keyword arguments.
            Required for parent class but unused
        Returns
        -------
        A tensor or list/tuple of tensors.
            The layer output
        """
        raise NotImplementedError()
 </s> add         var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        class:`numpy.ndarray`
            The normalized images for feeding to the model
          **kwargs: Additional keyword arguments.
              Required for parent class but unused
          Returns
          -------
        class:`numpy.ndarray`
            The normalized images for feeding to the model
        class:`numpy.ndarray`
            The normalized images for feeding to the model
          """
          return inputs[0] / inputs[1]
  
  
  class S3fd(KSession):
keep keep keep keep replace replace keep keep keep keep keep
 extract: S3FD - Convert to re-enable CPU 
plugins/extract/detect/s3fd.py