code: def testAssertValidSample(self):
      dist = truncated_normal.TruncatedNormal(
          loc=0.0, scale=2.0, low=-4.0, high=3.0, validate_args=True
      )
      with self.assertRaisesOpError(
          "must be greater than or equal to `low`"
      ):
          self.evaluate(dist.cdf([-4.2, 1.7, 2.3]))
      with self.assertRaisesOpError(
          "must be less than or equal to `high`"
      ):
          self.evaluate(dist.survival_function([2.3, -3.2, 4.0]))
  
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 9 for calling the TruncatedNormalStandaloneTestCase obj's underlying member method code with example usage: obj.testAssertValidSample() without return types