code: def test_from_stats(self):
      num_counts = 10.0
      mean = 1.0
      variance = 3.0
      var = sample_stats.RunningVariance.from_stats(
          num_counts, mean, variance
      )
      self.assertEqual(self.evaluate(var.mean), mean)
      self.assertEqual(self.evaluate(var.variance()), variance)
  
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 1 for calling the RunningCovarianceTest obj's underlying member method code with example usage: obj.test_from_stats() without return types