code: def test_zero_running_covariance(self):
      fake_samples = [[0.0, 0.0] for _ in range(2)]
      cov = sample_stats.RunningCovariance.from_shape((2,))
      for sample in fake_samples:
          cov = cov.update(sample)
      final_mean, final_cov = self.evaluate(
          [cov.mean, cov.covariance()]
      )
      self.assertAllClose([0.0, 0.0], final_mean, rtol=1e-5)
      self.assertAllCloseNested(np.zeros((2, 2)), final_cov)
  
imports: from absl.testing import parameterized
  import numpy
  import scipy.stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import diagnostic
label_desc: Use image node_id 5 for calling the RunningCovarianceTest obj's underlying member method code with example usage: obj.test_zero_running_covariance() without return types