code: def testKumaraswamyVariance(self):
      a = [1.0, 2, 3]
      b = [2.0, 4, 1.2]
      dist = kumaraswamy.Kumaraswamy(a, b, validate_args=True)
      expected_variance = (
          _kumaraswamy_moment(a, b, 2)
          - _kumaraswamy_moment(a, b, 1) ** 2
      )
      self.assertEqual((3,), dist.variance().shape)
      self.assertAllClose(
          expected_variance, self.evaluate(dist.variance())
      )
  
imports: import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import kumaraswamy
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 15 for calling the KumaraswamyTest obj's underlying member method code with example usage: obj.testKumaraswamyVariance() without return types