code: def testProbAndGradGivesFiniteResultsForCommonEvents(self):
      def quantized_log_prob(mu, sigma):
          x = tf.math.ceil(4 * rng.rand(100).astype(np.float32) - 2)
  
          qdist = qd.QuantizedDistribution(
              distribution=normal.Normal(loc=mu, scale=sigma),
              validate_args=True,
          )
          return qdist.log_prob(x)
  
      mu = tf.constant(0.0, name="mu")
      sigma = tf.constant(1.0, name="sigma")
  
      value, grads = self.evaluate(
          gradient.value_and_gradient(quantized_log_prob, [mu, sigma])
      )
      self.assertAllFinite(value)
      self.assertAllFinite(grads)
  
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 15 for calling the QuantizedDistributionTest obj's underlying member method code with example usage: obj.testProbAndGradGivesFiniteResultsForCommonEvents() and returns: qdist