code: def testPMFWithBatch(self):
      histograms = [[0.2, 0.8], [0.6, 0.4]]
      dist = categorical.Categorical(math_ops.log(histograms) - 50.0)
      with self.cached_session():
          self.assertAllClose(dist.prob([0, 1]), [0.2, 0.4])
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.eager import backprop
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gradients_impl
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops.distributions import categorical
  from tensorflow.python.ops.distributions import kullback_leibler
  from tensorflow.python.ops.distributions import normal
  from tensorflow.python.platform import test
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