code: def testPmfUnderflow(self):
      logits = np.array([[-200, 0]], dtype=np.float32)
      dist = multinomial.Multinomial(
          total_count=1.0, logits=logits, validate_args=True
      )
      lp = self.evaluate(dist.log_prob([1.0, 0.0]))[0]
      self.assertAllClose(-200, lp, atol=0, rtol=1e-6)
  
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 7 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testPmfUnderflow() without return types