code: def forward_gpu(self, inputs):
      x = inputs[0]
      b, c, h, w = x.shape
  
      y = cuda.cupy.empty_like(x)
      cuda.elementwise(
          "raw T x, int32 c, int32 h, int32 w,"
          "int32 kh, int32 kw,"
          "int32 dy, int32 dx",
          "T y",
          """
                 int b0 = i / (c * h * w);
                 int rest = i % (c * h * w);
                 int c0 = rest / (h * w);
                 rest %= h * w;
                 int out_row = rest / w;
                 int out_col = rest % w;
  
                 int n_groups = kh * kw;
                 int group_size = c / n_groups;
                 int group_idx = c0 / group_size;
                 // Make sure that center group is last
                 if (group_idx == (n_groups - 1) / 2) {
                    group_idx = n_groups - 1;
                 } else if (group_idx == n_groups - 1) {
                    group_idx = (n_groups - 1) / 2;
                 }
  
                 int ky = (group_idx / kw) - kh / 2;
                 int kx = (group_idx % kw) - kw / 2;
                 if (group_idx >= n_groups) {
                    ky = 0;
                    kx = 0;
                 }
  
                 int in_row = -ky * dy + out_row;
                 int in_col = -kx * dx + out_col;
                 if (in_row >= 0 && in_row < h && in_col >= 0 && in_col < w) {
                   y = x[b0 * c * h * w + c0 * h * w + in_row * w + in_col];
                 } else {
                   y = 0;
                 }
              """,
          "shift_gpu",
      )(x, c, h, w, self.kh, self.kw, self.dy, self.dx, y)
      return (y,)
  
file_path: chainer/chainer/functions/connection/shift.py
imports: import numpy
  from chainer.backends import cuda
  from chainer import function_node
  from chainer.utils import type_check
label_desc: Use image node_id 4 for calling the Shift obj's underlying member method code with example usage: obj.forward_gpu(inputs) and returns: y