code: def test_shift_in_running_covariance(self):
      rng = test_util.test_np_rng()
      x = rng.rand(100, 10) * 10
      shifted_x = x + 1e4
      cov = sample_stats.RunningCovariance.from_shape((10,))
      cov = consume(cov, x)
      shifted_cov = sample_stats.RunningCovariance.from_shape((10,))
      shifted_cov = consume(shifted_cov, shifted_x)
      final_cov, final_shifted_cov = self.evaluate(
          [cov.covariance(), shifted_cov.covariance()]
      )
      self.assertAllClose(final_cov, np.cov(x.T, ddof=0), rtol=1e-5)
      self.assertAllClose(
          final_shifted_cov, np.cov(x.T, ddof=0), rtol=1e-1
      )
  
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 10 for calling the RunningCovarianceTest obj's underlying member method code with example usage: obj.test_shift_in_running_covariance() without return types