code: def testCDFWithBatch(self):
      histograms = [
          [0.1, 0.2, 0.3, 0.25, 0.15],
          [0.0, 0.75, 0.2, 0.05, 0.0],
      ]
      event = [0, 3]
      expected_cdf = [0.0, 0.95]
      dist = categorical.Categorical(probs=histograms)
      cdf_op = dist.cdf(event)
  
      with self.cached_session():
          self.assertAllClose(cdf_op, expected_cdf)
  
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 10 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testCDFWithBatch() without return types