code: def testModifiedVariableAssertion(self):
      low = tf.Variable(0.0)
      peak = tf.Variable(0.5)
      high = tf.Variable(1.0)
      self.evaluate(
          [low.initializer, peak.initializer, high.initializer]
      )
      dist = triangular.Triangular(
          low=low, peak=peak, high=high, validate_args=True
      )
      with self.assertRaisesOpError("low > peak"):
          with tf.control_dependencies([low.assign(0.6)]):
              self.evaluate(dist.mean())
      with self.assertRaisesOpError("peak > high"):
          with tf.control_dependencies(
              [low.assign(0.0), peak.assign(1.2)]
          ):
              self.evaluate(dist.mean())
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import triangular
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 24 for calling the _TriangularTest obj's underlying member method code with example usage: obj.testModifiedVariableAssertion() without return types