code: def make_categorical_dist(self, is_gpu=False):
      p = numpy.random.normal(size=self.shape + (3,)).astype(
          numpy.float32
      )
      p = numpy.exp(p)
      p /= numpy.expand_dims(p.sum(axis=-1), axis=-1)
      params = self.encode_params({"p": p}, is_gpu)
      return distributions.Categorical(**params)
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import distributions
  from chainer import testing
  from chainer.testing import attr
label_desc: Use image node_id 5 for calling the TestKLDivergence obj's underlying member method code with example usage: obj.make_categorical_dist(is_gpu) and returns: distributions