code: def testVariableBounds(self):
      dist = normal.Normal(0.0, scale=2.0)
      low = tf.Variable(3.0)
      high = tf.Variable(-2.0)
      self.evaluate([v.initializer for v in [low, high]])
      with self.assertRaisesOpError("must be strictly less than"):
          d = qd.QuantizedDistribution(
              dist, low=low, high=high, validate_args=True
          )
          self.evaluate(d.sample(seed=test_util.test_seed()))
  
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 21 for calling the QuantizedDistributionTest obj's underlying member method code with example usage: obj.testVariableBounds() without return types