code: def check_im2col_nd(self, ksize, stride, pad, gpu):
      dims = self.dims
      if gpu:
          img = cuda.to_gpu(self.img)
      else:
          img = self.img
  
      col = conv_nd.im2col_nd(img, ksize, stride, pad)
      outs = tuple(
          conv_nd.get_conv_outsize(d, k, s, p)
          for (d, k, s, p) in zip(dims, ksize, stride, pad)
      )
      expected_shape = (2, 3) + ksize + outs
      self.assertEqual(col.shape, expected_shape)
  
      col = cuda.to_cpu(col)
  
      for n in moves.range(2):
          for c in moves.range(3):
              for xs in itertools.product(
                  *[moves.range(out) for out in outs]
              ):
                  for dxs in itertools.product(
                      *[moves.range(k) for k in ksize]
                  ):
                      oxs = tuple(
                          x * s - p + dx
                          for (x, s, p, dx) in zip(xs, stride, pad, dxs)
                      )
                      if all(0 <= ox < d for (ox, d) in zip(oxs, dims)):
                          col_index = (n, c) + dxs + xs
                          img_index = (n, c) + oxs
                          self.assertEqual(
                              col[col_index], self.img[img_index]
                          )
                      else:
                          col_index = (n, c) + dxs + xs
                          self.assertEqual(col[col_index], 0)
  
imports: import itertools
  import unittest
  import numpy
  from six import moves
  from chainer.backends import cuda
  from chainer import testing
  from chainer.testing import attr
  from chainer.utils import conv_nd
label_desc: Use image node_id 2 for calling the TestIm2ColND obj's underlying member method code with example usage: obj.check_im2col_nd(ksize, stride, pad, gpu) without return types