code: def ten_crop(img, size):
      """Crop 10 regions from an array.
  
      This method crops 10 regions. All regions will be in shape
      :obj:`size`. These regions consist of 1 center crop and 4 corner
      crops and horizontal flips of them.
  
      The crops are ordered in this order.
  
      * center crop
      * top-left crop
      * bottom-left crop
      * top-right crop
      * bottom-right crop
      * center crop (flipped horizontally)
      * top-left crop (flipped horizontally)
      * bottom-left crop (flipped horizontally)
      * top-right crop (flipped horizontally)
      * bottom-right crop (flipped horizontally)
  
      Args:
          img (~numpy.ndarray): An image array to be cropped. This is in
              CHW format.
          size (tuple): The size of output images after cropping.
              This value is :math:`(height, width)`.
  
      Returns:
          The cropped arrays. The shape of tensor is :math:`(10, C, H, W)`.
  
      """
      H, W = size
      iH, iW = img.shape[1:3]
  
      if iH < H or iW < W:
          raise ValueError(
              "shape of image is smaller than output shape"
          )
  
      crops = np.stack(
          (
              img[
                  :,
                  (iH - H) // 2 : (iH + H) // 2,
                  (iW - W) // 2 : (iW + W) // 2,
              ],
              img[:, 0:H, 0:W],
              img[:, iH - H : iH, 0:W],
              img[:, 0:H, iW - W : iW],
              img[:, iH - H : iH, iW - W : iW],
          )
      )
  
      crops = np.vstack((crops, crops[:, :, :, ::-1]))
  
      return crops
  
label_desc: Use image node_id 1 for calling a global function with example usage: ten_crop(img, size) and returns: crops