code: def testLogPMF(self):
      logits = np.log(np.array([[0.2, 0.8], [0.6, 0.4]])) - 50.0
      dist = categorical.Categorical(logits, validate_args=True)
      self.assertAllClose(
          np.log(np.array([0.2, 0.4])),
          self.evaluate(dist.log_prob([0, 1])),
      )
      self.assertAllClose(
          np.log(np.array([0.2, 0.4])),
          self.evaluate(dist.log_prob([0.0, 1.0])),
      )
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  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 15 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testLogPMF() without return types