code: def testVarianceAndStd(self):
      prob = [[0.2, 0.7], [0.8, 0.4]]
      dist = continuous_bernoulli.ContinuousBernoulli(
          probs=prob, validate_args=True
      )
      self.assertAllClose(
          self.evaluate(dist.variance()),
          np.array(
              [[var(0.2), var(0.7)], [var(0.8), var(0.4)]],
              dtype=np.float32,
          ),
          rtol=1e-5,
      )
      self.assertAllClose(
          self.evaluate(dist.stddev()),
          np.array(
              [
                  [np.sqrt(var(0.2)), np.sqrt(var(0.7))],
                  [np.sqrt(var(0.8)), np.sqrt(var(0.4))],
              ],
              dtype=np.float32,
          ),
          rtol=1e-5,
      )
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import continuous_bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 24 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj.testVarianceAndStd() without return types