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