code: def testLogProbCountsValid(self):
      d = beta_binomial.BetaBinomial(
          [10.0, 4.0], 1.0, 1.0, validate_args=True
      )
      d.log_prob([0.0, 0.0])
      d.log_prob([0.0, 2.0])
      d.log_prob([2.0, 4.0])
      d.log_prob([10.0, 4.0])
      with self.assertRaisesOpError("must be non-negative."):
          d.log_prob([-1.0, 3.0])
      with self.assertRaisesOpError(
          "cannot contain fractional components."
      ):
          self.evaluate(d.log_prob([3.0, 3.5]))
      with self.assertRaisesOpError(
          "must be itemwise less than or equal to `total_count` parameter."
      ):
          d.log_prob(5.0)
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import beta_binomial
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 10 for calling the BetaBinomialTest obj's underlying member method code with example usage: obj.testLogProbCountsValid() without return types