code: def testMeanDoubleTwoVotes(self):
      # The probabilities of two votes falling into class k for
      # DirichletMultinomial(2, alpha) is twice as much as the probability of one
      # vote falling into class k for DirichletMultinomial(1, alpha)
      alpha = [1.0, 2, 3]
      dist1 = dm.DirichletMultinomial(1.0, alpha, validate_args=True)
      dist2 = dm.DirichletMultinomial(2.0, alpha, validate_args=True)
  
      mean1 = self.evaluate(dist1.mean())
      mean2 = self.evaluate(dist2.mean())
      self.assertAllEqual([3], mean1.shape)
  
      for class_num in range(3):
          self.assertAllClose(mean2[class_num], 2 * mean1[class_num])
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import dirichlet_multinomial
  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 DirichletMultinomialTest obj's underlying member method code with example usage: obj.testMeanDoubleTwoVotes() without return types