code: def test_importance_prior(self):
      posterior = pyro.infer.Importance(
          self.model, guide=None, num_samples=10000
      ).run()
      marginal = EmpiricalMarginal(posterior)
      assert_equal(
          0, torch.norm(marginal.mean - self.loc_mean).item(), prec=0.01
      )
      assert_equal(
          0,
          torch.norm(marginal.variance.sqrt() - self.loc_stddev).item(),
          prec=0.1,
      )
  
file_path: pyro/tests/infer/test_sampling.py
imports: from unittest import TestCase
  import pytest
  import torch
  import pyro
  import pyro.infer
  from pyro.distributions import Bernoulli, Normal
  from pyro.infer import EmpiricalMarginal
  from tests.common import assert_equal
label_desc: Use image node_id 2 for calling the ImportanceTest obj's underlying member method code with example usage: obj.test_importance_prior() without return types