code: def check_backward(self, inputs, grad_outputs, backend_config):
      inputs = backend_config.get_array(inputs)
      grad_outputs = backend_config.get_array(grad_outputs)
      if not self.c_contiguous:
          with backend_config:
              inputs = _as_noncontiguous_array(inputs)
              grad_outputs = _as_noncontiguous_array(grad_outputs)
  
      def f(*inputs):
          y = functions.fixed_batch_normalization(*inputs, eps=self.eps)
          return (y,)
  
      with backend_config:
          gradient_check.check_backward(
              f, inputs, grad_outputs, **self.check_backward_options
          )
  
imports: import unittest
  import warnings
  import numpy
  import six
  import chainer
  from chainer.backends import cuda
  from chainer import functions
  from chainer import gradient_check
  from chainer import testing
  from chainer.testing import attr
  from chainer.testing import backend
label_desc: Use image node_id 6 for calling the TestFixedBatchNormalization obj's underlying member method code with example usage: obj.check_backward(inputs, grad_outputs, backend_config) and returns: y