code: def testLogits(self):
      p = np.array([0.2, 0.8], dtype=np.float32)
      logits = np.log(p) - 50.0
      dist = categorical.Categorical(logits=logits)
      with self.cached_session():
          self.assertAllEqual([2], dist.probs.get_shape())
          self.assertAllEqual([2], dist.logits.get_shape())
          self.assertAllClose(dist.probs, p)
          self.assertAllClose(dist.logits, logits)
  
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 2 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testLogits() without return types