code: def make_normal_dist(self, is_gpu=False, use_log_scale=False):
      loc = numpy.random.uniform(-1, 1, self.shape).astype(
          numpy.float32
      )
      if use_log_scale:
          log_scale = numpy.random.uniform(-1, 1, self.shape).astype(
              numpy.float32
          )
          params = self.encode_params(
              {"loc": loc, "log_scale": log_scale}, is_gpu
          )
      else:
          scale = numpy.exp(
              numpy.random.uniform(-1, 1, self.shape)
          ).astype(numpy.float32)
          params = self.encode_params(
              {"loc": loc, "scale": scale}, is_gpu
          )
      return distributions.Normal(**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 13 for calling the TestKLDivergence obj's underlying member method code with example usage: obj.make_normal_dist(is_gpu, use_log_scale) and returns: distributions