code: def test_running_variance(self, ddof):
      rng = test_util.test_np_rng()
      x = rng.rand(100)
      var = sample_stats.RunningVariance.from_shape()
      var = consume(var, x)
      final_mean, final_var = self.evaluate(
          [var.mean, var.variance(ddof=ddof)]
      )
      self.assertNear(np.mean(x), final_mean, err=1e-6)
      self.assertNear(np.var(x, ddof=ddof), final_var, err=1e-6)
  
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 2 for calling the RunningCovarianceTest obj's underlying member method code with example usage: obj.test_running_variance(ddof) without return types