code: def test_autocovariance():
      x = torch.arange(10.0)
      with xfail_if_not_implemented():
          actual = autocovariance(x)
      assert_equal(
          actual,
          torch.tensor(
              [
                  8.25,
                  6.42,
                  4.25,
                  1.75,
                  -1.08,
                  -4.25,
                  -7.75,
                  -11.58,
                  -15.75,
                  -20.25,
              ]
          ),
          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 12 for calling a global function with example usage: test_autocovariance() without return types