code: def testPmfBothZeroBatchesNontrivialN(self):
      # The probabilities of one vote falling into class k is the mean for class
      # k.
      # Both zero-batches.  No broadcast
      alpha = [1.0, 2]
      counts = [3.0, 2]
      dist = dm.DirichletMultinomial(5.0, alpha, validate_args=True)
      pmf = dist.prob(counts)
      self.assertAllClose(1 / 7.0, self.evaluate(pmf))
      self.assertEqual((), 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 9 for calling the DirichletMultinomialTest obj's underlying member method code with example usage: obj.testPmfBothZeroBatchesNontrivialN() without return types