code: def testEntropyWithBatch(self):
      logits = np.log([[0.2, 0.8], [0.6, 0.4]]) - 50.0
      dist = categorical.Categorical(logits)
      with self.cached_session():
          self.assertAllClose(
              dist.entropy(),
              [
                  -(0.2 * np.log(0.2) + 0.8 * np.log(0.8)),
                  -(0.6 * np.log(0.6) + 0.4 * np.log(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 16 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testEntropyWithBatch() without return types