code: def testParetoMean(self):
      scale = [1.4, 2.0, 2.5]
      concentration = [2.0, 3.0, 2.5]
      dist = pareto.Pareto(concentration, scale, validate_args=True)
      self.assertEqual(dist.mean().shape, (3,))
      self.assertAllClose(
          self.evaluate(dist.mean()),
          self._scipy_pareto(concentration, scale).mean(),
      )
  
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 13 for calling the ParetoTest obj's underlying member method code with example usage: obj.testParetoMean() without return types