code: def testZipfSampleMultidimensionalStd(self):
      power_v = np.array([np.arange(5, 10, dtype=np.float32)])  # 1 x 5
      dist = zipf.Zipf(power=power_v, validate_args=True)
      n = int(100e4)
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      self.assertEqual((n, 1, 5), samples.shape)
      self.assertEqual((n, 1, 5), sample_values.shape)
  
      # stats.zipf wants float64 params.
      stats_std = np.vectorize(stats.zipf.std)(
          power_v.astype(np.float64)
      )
      self.assertAllClose(
          sample_values.std(axis=0), stats_std, rtol=0.04
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import zipf
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 28 for calling the ZipfTest obj's underlying member method code with example usage: obj.testZipfSampleMultidimensionalStd() without return types