code: def testN(self):
      p = [[0.1, 0.2, 0.7], [0.2, 0.3, 0.5]]
      n = [[3.0], [4]]
      dist = multinomial.Multinomial(
          total_count=n, probs=p, validate_args=True
      )
      self.assertAllEqual([2, 1], dist.total_count.shape)
      self.assertAllClose(n, self.evaluate(dist.total_count))
  
imports: import unittest
  from absl.testing import parameterized
  import hypothesis
  from hypothesis import strategies
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import binomial
  from tensorflow_probability.python.distributions import hypothesis_testlib
  from tensorflow_probability.python.distributions import multinomial
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 4 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testN() without return types