code: def testParetoLogPdfValidateArgs(self):
      batch_size = 3
      scale = tf.constant([2.0, 3.0, 4.0])
      concentration = tf.constant([2.0] * batch_size)
      dist = pareto.Pareto(concentration, scale, validate_args=True)
  
      with self.assertRaisesOpError("not in the support"):
          x = tf1.placeholder_with_default([2.0, 3.0, 3.0], shape=[3])
          log_prob = dist.log_prob(x)
          self.evaluate(log_prob)
  
      with self.assertRaisesOpError("not in the support"):
          x = tf1.placeholder_with_default([2.0, 2.0, 5.0], shape=[3])
          log_prob = dist.log_prob(x)
          self.evaluate(log_prob)
  
      with self.assertRaisesOpError("not in the support"):
          x = tf1.placeholder_with_default([1.0, 3.0, 5.0], shape=[3])
          log_prob = dist.log_prob(x)
          self.evaluate(log_prob)
  
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 7 for calling the ParetoTest obj's underlying member method code with example usage: obj.testParetoLogPdfValidateArgs() without return types