code: def testPmfForOneVoteIsTheMeanWithOneRecordInput(self):
      # The probabilities of one vote falling into class k is the mean for class
      # k.
      alpha = [1.0, 2, 3]
      with self.cached_session():
          for class_num in range(3):
              counts = np.zeros([3], dtype=np.float32)
              counts[class_num] = 1
              dist = ds.DirichletMultinomial(1.0, alpha)
              mean = dist.mean().eval()
              pmf = dist.prob(counts).eval()
  
              self.assertAllClose(mean[class_num], pmf)
              self.assertAllEqual([3], mean.shape)
              self.assertAllEqual([], pmf.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 15 for calling the DirichletMultinomialTest obj's underlying member method code with example usage: obj.testPmfForOneVoteIsTheMeanWithOneRecordInput() without return types