code: def testLogisticLogProbThatUsedToUnderflowNoLongerDoes(self):
      # At integer values, the result should be the same as the standard normal.
      dist = logistic.Logistic(loc=0.06602609, scale=4.8474164)
      low = -32768.0
      high = 32768.0
      y = -0.062469486 * 32768.0
      qdist = qd.QuantizedDistribution(dist, low=low, high=high)
      log_prob = qdist.log_prob(y)
      self.assertTrue(np.isfinite(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 exponential
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import quantized_distribution
  from tensorflow_probability.python.distributions import uniform
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 8 for calling the QuantizedDistributionTest obj's underlying member method code with example usage: obj.testLogisticLogProbThatUsedToUnderflowNoLongerDoes() without return types