code: def test_effective_sample_size():
      x = torch.arange(1000.0).reshape(100, 10)
  
      with xfail_if_not_implemented():
          # test against arviz
          assert_equal(
              effective_sample_size(x).item(), 52.64, prec=0.01
          )
  
imports: import warnings
  import pytest
  import torch
  from pyro.ops.stats import _cummin, autocorrelation, autocovariance, crps_empirical, effective_sample_size, fit_generalized_pareto, gelman_rubin, hpdi, pi, quantile, resample, split_gelman_rubin, waic
  from tests.common import assert_close, assert_equal, xfail_if_not_implemented
label_desc: Use image node_id 17 for calling a global function with example usage: test_effective_sample_size() without return types