code: def testPMFWithBatch(self):
      histograms = np.array([[0.2, 0.8], [0.6, 0.4]])
      dist = categorical.Categorical(
          tf.math.log(histograms) - 50.0, validate_args=True
      )
      self.assertAllClose([0.2, 0.4], self.evaluate(dist.prob([0, 1])))
  
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 6 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testPMFWithBatch() without return types