code: def testParetoVarianceInf(self):
      scale = [1.4, 2.0, 2.5]
      concentration = [0.4, 0.9, 0.99]
      dist = pareto.Pareto(concentration, scale, validate_args=True)
      self.assertEqual(dist.variance().shape, (3,))
      self.assertTrue(np.all(np.isinf(self.evaluate(dist.variance()))))
  
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 16 for calling the ParetoTest obj's underlying member method code with example usage: obj.testParetoVarianceInf() without return types