code: def testMean(self):
      prob = np.array([[0.2, 0.7], [0.8, 0.4]], dtype=np.float32)
      dist = continuous_bernoulli.ContinuousBernoulli(
          probs=prob, validate_args=True
      )
      self.assertAllClose(self.evaluate(dist.mean()), mean(prob))
  
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 20 for calling the ContinuousBernoulliTest obj's underlying member method code with example usage: obj.testMean() without return types