code: def testBetaMeanAfterMutation(self):
      concentration1 = tf.Variable(2.0)
      concentration0 = tf.Variable(3.0)
      self.evaluate(concentration1.initializer)
      self.evaluate(concentration0.initializer)
      dist = beta.Beta(
          concentration1=concentration1,
          concentration0=concentration0,
          validate_args=True,
      )
      with tf.control_dependencies([concentration0.assign(6.0)]):
          mean = self.evaluate(dist.mean())
          self.assertEqual(mean, 0.25)
  
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 30 for calling the BetaTest obj's underlying member method code with example usage: obj.testBetaMeanAfterMutation() without return types