code: def window_reverse(windows, window_size, b, d, h, w):
      """
      Args:
          windows (`torch.Tensor`):
              Tensor with size (B*num_windows, window_size, window_size, C)
          window_size (`tuple[int]`):
              3D window size.
          b (`int`):
              Batch size
          d (`int`):
              Window size in time dimension.
          h (`int`):
              Height of image
          w (`int`):
              Width of image
      Returns:
          x (`torch.Tensor`):
              Tensor with size (b, d, h, w, c)
      """
      x = windows.view(
          b,
          d // window_size[0],
          h // window_size[1],
          w // window_size[2],
          window_size[0],
          window_size[1],
          window_size[2],
          -1,
      )
      x = (
          x.permute(0, 1, 4, 2, 5, 3, 6, 7)
          .contiguous()
          .view(b, d, h, w, -1)
      )
      return x
  
label_desc: Use image node_id 1 for calling a global function with example usage: window_reverse(windows, window_size, b, d, h, w) and returns: x