def METHOD_NAME(self, input, t, **kwargs):
    if t.dtype != torch.int64 and t.dtype != torch.int32:
        t = t.round()
    sigma = self.t_to_sigma(t)
    input = input * ((utils.append_dims(sigma, input.ndim) ** 2 + 1.0) ** 0.5)
    return  (input - self(input, sigma, **kwargs)) / utils.append_dims(sigma, input.ndim)