code: def testParetoSampleMean(self):
      scale = 4.0
      concentration = 3.0
      n = int(100e3)
      dist = pareto.Pareto(concentration, scale, validate_args=True)
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
      self.assertEqual(samples.shape, (n,))
      self.assertEqual(sample_values.shape, (n,))
      self.assertAllClose(
          sample_values.mean(),
          self._scipy_pareto(concentration, scale).mean(),
          rtol=0.01,
          atol=0,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import pareto
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 19 for calling the ParetoTest obj's underlying member method code with example usage: obj.testParetoSampleMean() without return types