code: def testModifiedVariableAssertionSingleVar(self):
      low = tf.Variable(0.0)
      high = 1.0
      self.evaluate(low.initializer)
      dist = uniform.Uniform(low=low, high=high, validate_args=True)
      with self.assertRaisesOpError("not defined when `low` >= `high`"):
          with tf.control_dependencies([low.assign(2.0)]):
              self.evaluate(dist.mean())
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kullback_leibler
  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 25 for calling the UniformTest obj's underlying member method code with example usage: obj.testModifiedVariableAssertionSingleVar() without return types