code: def testPmfBothZeroBatchesNontrivialN(self):
      with self.cached_session():
          # Both zero-batches.  No broadcast
          p = [0.1, 0.9]
          counts = [3.0, 2]
          dist = multinomial.Multinomial(total_count=5.0, probs=p)
          pmf = dist.prob(counts)
          # 5 choose 3 = 5 choose 2 = 10. 10 * (.9)^2 * (.1)^3 = 81/10000.
          self.assertAllClose(81.0 / 10000, self.evaluate(pmf))
          self.assertEqual((), pmf.get_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 multinomial
  from tensorflow.python.platform import test
label_desc: Use image node_id 11 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testPmfBothZeroBatchesNontrivialN() without return types