code: def testLogits(self):
      p = np.array([[0.1, 0.2, 0.7]], dtype=np.float32)
      logits = np.log(p) - 50.0
      multinom = multinomial.Multinomial(
          total_count=3.0, logits=logits, validate_args=True
      )
      self.assertAllEqual([1, 3], multinom.probs_parameter().shape)
      self.assertAllEqual([1, 3], multinom.logits_parameter().shape)
      self.assertAllClose(p, self.evaluate(multinom.probs_parameter()))
      self.assertAllClose(
          logits, self.evaluate(multinom.logits_parameter())
      )
  
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 6 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testLogits() without return types