          f5_3 = L2Norm(512, scale=5, name="conv5_3_norm")(f5_3)
  
  
          f4_3 = ZeroPadding2D(1)(f4_3)
          cls2 = Conv2D(2, kernel_size=3, strides=1, name="conv4_3_norm_mbox_conf")(f4_3)
          reg2 = Conv2D(4, kernel_size=3, strides=1, name="conv4_3_norm_mbox_loc")(f4_3)
  
          f5_3 = ZeroPadding2D(1)(f5_3)
 
</s> remove class SqrtO2K(keras.layers.Layer):  # pylint:disable=too-few-public-methods
    """ Custom Keras Square Root layer generated by onnx2keras. """
    def call(self, inputs, **kwargs):  # pylint:disable=unused-argument,no-self-use
        """This is where the layer's logic lives.
 </s> add         f4_3 = ZeroPadding2D(1)(f4_3)
        cls2 = Conv2D(2, kernel_size=3, strides=1, name="conv4_3_norm_mbox_conf")(f4_3)
        reg2 = Conv2D(4, kernel_size=3, strides=1, name="conv4_3_norm_mbox_loc")(f4_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
        """
        return K.sqrt(inputs)
 </s> add         f5_3 = ZeroPadding2D(1)(f5_3)
        cls3 = Conv2D(2, kernel_size=3, strides=1, name="conv5_3_norm_mbox_conf")(f5_3)
        reg3 = Conv2D(4, kernel_size=3, strides=1, name="conv5_3_norm_mbox_loc")(f5_3) </s> remove class PowO2K(keras.layers.Layer):  # pylint:disable=too-few-public-methods
    """ Custom Keras Power layer generated by onnx2keras. """
    def call(self, inputs, **kwargs):  # pylint:disable=unused-argument,no-self-use
        """This is where the layer's logic lives.
 </s> add         f6_2 = ZeroPadding2D(1)(f6_2)
        cls5 = Conv2D(2, kernel_size=3, strides=1, name="conv6_2_mbox_conf")(f6_2)
        reg5 = Conv2D(4, kernel_size=3, strides=1, name="conv6_2_mbox_loc")(f6_2)
        f3_3 = ZeroPadding2D(1)(f3_3)
        cls1 = Conv2D(4, kernel_size=3, strides=1, name="conv3_3_norm_mbox_conf")(f3_3)
        reg1 = Conv2D(4, kernel_size=3, strides=1, name="conv3_3_norm_mbox_loc")(f3_3)
          f5_3 = L2Norm(512, scale=5, name="conv5_3_norm")(f5_3)
  
        f3_3 = ZeroPadding2D(1)(f3_3)
        cls1 = Conv2D(4, kernel_size=3, strides=1, name="conv3_3_norm_mbox_conf")(f3_3)
        reg1 = Conv2D(4, kernel_size=3, strides=1, name="conv3_3_norm_mbox_loc")(f3_3)
  
          f4_3 = ZeroPadding2D(1)(f4_3)
          cls2 = Conv2D(2, kernel_size=3, strides=1, name="conv4_3_norm_mbox_conf")(f4_3)
          reg2 = Conv2D(4, kernel_size=3, strides=1, name="conv4_3_norm_mbox_loc")(f4_3)
  
          f5_3 = ZeroPadding2D(1)(f5_3)
keep add keep keep keep keep keep keep
 extract: S3FD - Convert to re-enable CPU 
plugins/extract/detect/s3fd.py