def METHOD_NAME(self):
    for _ in range(4):
        prob, prob2 = np.random.uniform(0,1), np.random.uniform(0,1)
        jg, jg2 = jd.Geometric(prob),jd.Geometric(prob2)
        tg, tg2 = torch.distributions.Geometric(prob),torch.distributions.Geometric(prob2)
        np.testing.assert_allclose(jg.entropy().data,tg.entropy().numpy(), atol=1e-4)
        x = np.random.randint(1,10)
        np.testing.assert_allclose(jg.log_prob(x),tg.log_prob(torch.tensor(x)), atol=1e-4)
        # print(jd.kl_divergence(jg,jg2),torch.distributions.kl_divergence(tg,tg2))
        np.testing.assert_allclose(jd.kl_divergence(jg,jg2),torch.distributions.kl_divergence(tg,tg2), atol=1e-4)