code: def testBetaVariance(self):
      a = [1.0, 2, 3]
      b = [2.0, 4, 1.2]
      dist = beta.Beta(a, b, validate_args=True)
      self.assertEqual(dist.variance().shape, (3,))
      expected_variance = sp_stats.beta.var(a, b)
      self.assertAllClose(
          expected_variance, self.evaluate(dist.variance())
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import special
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import beta
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 16 for calling the BetaTest obj's underlying member method code with example usage: obj.testBetaVariance() without return types