code: def check_gaussian_kl_divergence(self, mean, ln_var):
      if self.wrap_m:
          mean = chainer.Variable(mean)
      if self.wrap_v:
          ln_var = chainer.Variable(ln_var)
      actual = cuda.to_cpu(
          F.gaussian_kl_divergence(mean, ln_var, self.reduce).data
      )
      actual = cuda.to_cpu(
          F.gaussian_kl_divergence(mean, ln_var, self.reduce).data
      )
      testing.assert_allclose(self.expect, actual)
  
imports: import unittest
  import numpy
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import condition
label_desc: Use image node_id 2 for calling the TestGaussianKLDivergence obj's underlying member method code with example usage: obj.check_gaussian_kl_divergence(mean, ln_var) without return types