def test_add(self):
        prio_set_list = event._PrioritizedSetList()
        objs = [(i,) for i in range(5)]

        prio_set_list.add(0, objs[0])
        assert prio_set_list.list == [(0, {objs[0]})]

        prio_set_list.add(0, objs[1])
        assert prio_set_list.list == [(0, {objs[0], objs[1]})]

        prio_set_list.add(10, objs[2])
        assert prio_set_list.list == [(10, {objs[2]}),
                                      (0,  {objs[0], objs[1]})]

        prio_set_list.add(-10, objs[3])
        assert prio_set_list.list == [( 10, {objs[2]}),           # noqa: E201
                                      (  0, {objs[0], objs[1]}),  # noqa: E201
                                      (-10, {objs[3]})]
        prio_set_list.add(-1, objs[4])
        assert prio_set_list.list == [( 10, {objs[2]}),           # noqa: E201
                                      (  0, {objs[0], objs[1]}),  # noqa: E201
                                      ( -1, {objs[4]}),           # noqa: E201
                                      (-10, {objs[3]})]
def __init__(self, train_x, train_y, likelihood):
        super(GPRegressionModel, self).__init__(train_x, train_y, likelihood)
        self.mean_module = ConstantMean(prior=SmoothedBoxPrior(-1e-5, 1e-5))
        self.base_covar_module = ScaleKernel(RBFKernel(lengthscale_prior=SmoothedBoxPrior(exp(-5), exp(6), sigma=0.1)))
        self.covar_module = InducingPointKernel(
            self.base_covar_module, inducing_points=torch.linspace(0, 1, 32), likelihood=likelihood
        )