code: def check_covariance(self, is_gpu):
      if is_gpu:
          cov1 = self.gpu_dist.covariance.array
      else:
          cov1 = self.cpu_dist.covariance.array
      cov2 = self.params["cov"]
      array.assert_allclose(cov1, cov2)
  
imports: import functools
  import itertools
  import operator
  import numpy
  from chainer import distributions
  from chainer import testing
  from chainer.testing import array
  from chainer.testing import attr
  from chainer import utils
label_desc: Use image node_id 5 for calling the TestIndependentNormal obj's underlying member method code with example usage: obj.check_covariance(is_gpu) without return types