code: def test_running_covariance(self, ddof):
      rng = test_util.test_np_rng()
      x = rng.rand(100, 10)
      cov = sample_stats.RunningCovariance.from_shape((10,))
      cov = consume(cov, x)
      final_mean, final_cov = self.evaluate(
          [cov.mean, cov.covariance(ddof=ddof)]
      )
      self.assertAllClose(np.mean(x, axis=0), final_mean, rtol=1e-5)
      self.assertAllClose(np.cov(x.T, ddof=ddof), final_cov, rtol=1e-5)
      self.assertEqual(cov.event_ndims, 1)
      self.assertEqual(cov.mean.dtype, tf.float32)
  
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 6 for calling the RunningCovarianceTest obj's underlying member method code with example usage: obj.test_running_covariance(ddof) without return types