code: def check_backward(self, s_data, i_data, x_data, gt_data):
      # We cannot use check_backward method as a thin stack reuses ndarray.
      gt_old = gt_data.copy()
      s = chainer.Variable(s_data)
      i = chainer.Variable(i_data)
      x = chainer.Variable(x_data)
      t = thin_stack.thin_stack_set(s, i, x)
      t.grad = gt_data
  
      t.backward()
      for j, ind in enumerate(i_data):
          testing.assert_allclose(x.grad[j], gt_old[j, ind])
          for k in range(self.shape[1]):
              if k == ind:
                  testing.assert_allclose(s.grad[j, k], 0)
              else:
                  testing.assert_allclose(s.grad[j, k], gt_old[j, k])
  
      self.assertIsNone(i.grad)
      # Thin stack reueses the same gradient array.
      self.assertIs(s.grad, gt_data)
  
imports: import unittest
  import numpy
  import chainer
  from chainer import backend
  from chainer import cuda
  from chainer import testing
  from chainer.testing import attr
  import thin_stack
label_desc: Use image node_id 5 for calling the TestThinStackSet obj's underlying member method code with example usage: obj.check_backward(s_data, i_data, x_data, gt_data) without return types