code: def testVariance(self):
      (
          temperature,
          low,
          peak,
          high,
          a,
          b,
      ) = self._generate_boilerplate_param()
      dist = pert.PERT(low, peak, high, temperature, validate_args=True)
      expected_var = sp_stats.beta.var(a, b, low, high - low)
      self.assertAllClose(expected_var, self.evaluate(dist.variance()))
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import pert
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import assert_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 8 for calling the PERTTest obj's underlying member method code with example usage: obj.testVariance() without return types