@abstractmethod<EOL><INDENT>def backward(self, gradient, image):<DEDENT>
raise NotImplementedError<EOL>
Backpropagates the gradient of some loss w.r.t. the logits
        through the network and returns the gradient of that loss w.r.t
        to the input image.

        Parameters
        ----------
        gradient : `numpy.ndarray`
            Gradient of some loss w.r.t. the logits.
        image : `numpy.ndarray`
            Single input with shape as expected by the model
            (without the batch dimension).

        Returns
        -------
        gradient : `numpy.ndarray`
            The gradient w.r.t the image.

        See Also
        --------
        :meth:`gradient`