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]
      with self.cached_session():
          for class_num in range(3):
              counts_one = np.zeros([3], dtype=np.float32)
              counts_one[class_num] = 1.0
              counts_two = np.zeros([3], dtype=np.float32)
              counts_two[class_num] = 2
  
              dist1 = ds.DirichletMultinomial(1.0, alpha)
              dist2 = ds.DirichletMultinomial(2.0, alpha)
  
              mean1 = dist1.mean().eval()
              mean2 = dist2.mean().eval()
  
              self.assertAllClose(
                  mean2[class_num], 2 * mean1[class_num]
              )
              self.assertAllEqual([3], mean1.shape)
  
imports: import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.distributions import dirichlet_multinomial
  from tensorflow.python.platform import test
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