code: def testMode(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.assertAllEqual([[1, 0]], self.evaluate(dist.mode()))
  
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 29 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testMode() without return types