test_sampling.py 文件源码

def test_importance_prior(self):
        posterior = pyro.infer.Importance(self.model, guide=None, num_samples=10000)
        marginal = pyro.infer.Marginal(posterior)
        posterior_samples = [marginal() for i in range(1000)]
        posterior_mean = torch.mean(torch.cat(posterior_samples))
        posterior_stddev = torch.std(torch.cat(posterior_samples), 0)
        self.assertEqual(0, torch.norm(posterior_mean - self.mu_mean).data[0],
                         prec=0.01)
        self.assertEqual(0, torch.norm(posterior_stddev - self.mu_stddev).data[0],
                         prec=0.1)