code: def test_mean(continuous_dist):
      Dist = continuous_dist.pyro_dist
      if Dist.__name__ in [
          "Cauchy",
          "HalfCauchy",
          "SineBivariateVonMises",
          "VonMises",
          "ProjectedNormal",
      ]:
          pytest.xfail(reason="Euclidean mean is not defined")
      for i in range(continuous_dist.get_num_test_data()):
          d = Dist(**continuous_dist.get_dist_params(i))
      with xfail_if_not_implemented():
          actual = d.mean
      num_samples = 100000
      if Dist.__name__ == "LogNormal":
          num_samples = 200000
      expected = d.sample((num_samples,)).mean(0)
      assert_close(actual, expected, atol=0.02, rtol=0.05)
  
imports: import numpy
  import pytest
  import torch
  import pyro
  import pyro.distributions
  from pyro.distributions import TorchDistribution
  from pyro.distributions.testing.gof import auto_goodness_of_fit
  from pyro.distributions.util import broadcast_shape
  from tests.common import TEST_FAILURE_RATE, assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 11 for calling a global function with example usage: test_mean(continuous_dist) without return types