def _broadcast(self, arys):
        """Perform numpy ufunc broadcasting
        """
        shapelist = [a.shape for a in arys]
        shape = _multi_broadcast(*shapelist)

        for i, ary in enumerate(arys):
            if ary.shape == shape:
                pass

            else:
                if self.is_device_array(ary):
                    arys[i] = self.broadcast_device(ary, shape)

                else:
                    ax_differs = [ax for ax in range(len(shape))
                                  if ax >= ary.ndim
                                  or ary.shape[ax] is shape[ax]]

                    missingdim = len(shape) - len(ary.shape)
                    strides = [0] * missingdim + list(ary.strides)

                    for ax in ax_differs:
                        strides[ax] = 0

                    strided = np.lib.stride_tricks.as_strided(ary,
                                                              shape=shape,
                                                              strides=strides)

                    arys[i] = self.force_array_layout(strided)

        return arys
dataset/ETHPy150Open numba/numba/numba/npyufunc/deviceufunc.py/UFuncMechanism._broadcast/operator `!=` -> `is`