code: def testLogProbOverflow(self):
      logits = np.float32([20.0, 30.0, 40.0])
      total_count = np.float32(1.0)
      x = np.float32(0.0)
      nb = negative_binomial.NegativeBinomial(
          total_count=total_count, logits=logits, validate_args=True
      )
      log_prob_ = self.evaluate(nb.log_prob(x))
      self.assertAllEqual(
          np.ones_like(log_prob_, dtype=np.bool_),
          np.isfinite(log_prob_),
      )
  
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 19 for calling the NegativeBinomialTest obj's underlying member method code with example usage: obj.testLogProbOverflow() without return types