code: def make_pareto_dist(self, is_gpu=False):
      scale = numpy.exp(
          numpy.random.uniform(0.5, 1, self.shape)
      ).astype(numpy.float32)
      alpha = numpy.exp(numpy.random.uniform(1, 2, self.shape)).astype(
          numpy.float32
      )
      params = self.encode_params(
          {"scale": scale, "alpha": alpha}, is_gpu
      )
      return distributions.Pareto(**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 16 for calling the TestKLDivergence obj's underlying member method code with example usage: obj.make_pareto_dist(is_gpu) and returns: distributions