code: def testNegativeSigmaFailsVarAssignment(self):
      dist = truncated_normal.TruncatedNormal(
          loc=0.0,
          scale=tf.Variable(0.1),
          low=-1.0,
          high=1.0,
          validate_args=True,
      )
      self.evaluate([v.initializer for v in dist.variables])
      self.evaluate(dist.mean())
      with tf.control_dependencies([dist.scale.assign(-0.1)]):
          with self.assertRaisesOpError("`scale` must be positive"):
              self.evaluate(dist.mean())
  
imports: import itertools
  import unittest
  from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import truncated_normal
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 12 for calling the TruncatedNormalStandaloneTestCase obj's underlying member method code with example usage: obj.testNegativeSigmaFailsVarAssignment() without return types