code: def testBetaVariance(self):
      a = [1.0, 2, 3]
      b = [2.0, 4, 1.2]
      dist = beta_lib.Beta(a, b)
      self.assertEqual(dist.variance().get_shape(), (3,))
      if not stats:
          return
      expected_variance = stats.beta.var(a, b)
      self.assertAllClose(
          expected_variance, self.evaluate(dist.variance())
      )
  
imports: import importlib
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.distributions import beta
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.platform import test
  from tensorflow.python.platform import tf_logging
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