code: def testNegativeBinomialLogPmfValidateArgs(self):
      batch_size = 6
      probs = [0.9] * batch_size
      total_count = 5.0
      x = tf1.placeholder_with_default(
          [2.5, 3.2, 4.3, 5.1, 6.0, 7.0], shape=[6]
      )
      negbinom = negative_binomial.NegativeBinomial(
          total_count=total_count, probs=probs, validate_args=True
      )
  
      with self.assertRaisesOpError(
          "cannot contain fractional components"
      ):
          self.evaluate(negbinom.log_prob(x))
  
      with self.assertRaisesOpError("Condition x >= 0"):
          self.evaluate(negbinom.log_prob([-1.0]))
  
      negbinom = negative_binomial.NegativeBinomial(
          total_count=total_count, probs=probs, validate_args=False
      )
      log_pmf = negbinom.log_prob(x)
      self.assertEqual([6], log_pmf.shape)
      pmf = negbinom.prob(x)
      self.assertEqual([6], pmf.shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import negative_binomial
  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 NegativeBinomialTest obj's underlying member method code with example usage: obj.testNegativeBinomialLogPmfValidateArgs() without return types