def backward(self, out_grads=None):
        """Backward computation.

        See Also
        ----------
        :meth:`BaseModule.backward`.

        Parameters
        ----------
        out_grads : NDArray or list of NDArray, optional
            Gradient on the outputs to be propagated back.
            This parameter is only needed when bind is called
            on outputs that are not a loss function.
        """
        super(SVRGModule, self).backward(out_grads)

        if self._mod_aux.binded:
            self._mod_aux.backward(out_grads)
Backward computation.

        See Also
        ----------
        :meth:`BaseModule.backward`.

        Parameters
        ----------
        out_grads : NDArray or list of NDArray, optional
            Gradient on the outputs to be propagated back.
            This parameter is only needed when bind is called
            on outputs that are not a loss function.