          """This is where the layer's logic lives.
  
          Override for layers which inherit from this class
  
          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()
  
  
  class SumO2K(ReduceLayerO2K):
      """ Custom Keras Sum layer generated by onnx2keras. """
      def call(self, inputs, **kwargs):  # pylint:disable=unused-argument
 
</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 class ElementwiseLayerO2K(keras.layers.Layer):
    """ Custom Keras Element Wise layer generated by onnx2keras. """
    def call(self, inputs, **kwargs):  # pylint:disable=unused-argument
        """This is where the layer's logic lives.

        Override for layers that inherit from this class.

        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()

    def compute_output_shape(self, input_shape):  # pylint:disable=no-self-use
        """Computes the output shape of the layer.
 </s> add class L2Norm(keras.layers.Layer):
    """ L2 Normalization layer for S3FD.

    Parameters
    ----------
    n_channels: int
        The number of channels to normalize
    scale: float, optional
        The scaling for initial weights. Default: `1.0`
    """
    def __init__(self, n_channels, scale=1.0, **kwargs):
        super().__init__(**kwargs)
        self._n_channels = n_channels
        self._scale = scale
        self.w = self.add_weight("l2norm",  # pylint:disable=invalid-name
                                 (self._n_channels, ),
                                 trainable=True,
                                 initializer=keras.initializers.Constant(value=self._scale),
                                 dtype="float32") </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.sum(inputs, self._axes, self._keepdims)
 </s> add         f3_3 = L2Norm(256, scale=10, name="conv3_3_norm")(f3_3)
        f4_3 = L2Norm(512, scale=8, name="conv4_3_norm")(f4_3)
        f5_3 = L2Norm(512, scale=5, name="conv5_3_norm")(f5_3) </s> remove class SumO2K(ReduceLayerO2K):
    """ Custom Keras Sum layer generated by onnx2keras. """
    def call(self, inputs, **kwargs):  # pylint:disable=unused-argument
        """This is where the layer's logic lives.
 </s> add         f6_2 = self.conv_up(var_x, 256, 6)
        f7_2 = self.conv_up(f6_2, 128, 7) </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)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
          """This is where the layer's logic lives.
  
          Override for layers which inherit from this class
  
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        var_x = self.conv_block(var_x, 512, 5, 3)
        f5_3 = var_x
        var_x = MaxPooling2D(pool_size=2, strides=2)(var_x)
        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 SumO2K(ReduceLayerO2K):
      """ Custom Keras Sum layer generated by onnx2keras. """
      def call(self, inputs, **kwargs):  # pylint:disable=unused-argument
keep keep keep keep replace replace replace replace replace replace replace replace replace replace replace replace keep keep keep keep keep
 extract: S3FD - Convert to re-enable CPU 
plugins/extract/detect/s3fd.py