code: def testVariableLowAfterMutation(self):
      dist = normal.Normal(0.0, scale=2.0)
      low = tf.Variable(-4.0)
      d = qd.QuantizedDistribution(
          dist, low=low, high=5.0, validate_args=True
      )
      self.evaluate(low.initializer)
      with self.assertRaisesOpError("must be strictly less than"):
          with tf.control_dependencies([low.assign(6.0)]):
              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 22 for calling the QuantizedDistributionTest obj's underlying member method code with example usage: obj.testVariableLowAfterMutation() without return types