code: def ten_crop(
      img: Tensor, size: List[int], vertical_flip: bool = False
  ) -> Tuple[
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
      Tensor,
  ]:
      """Generate ten cropped images from the given image.
      Crop the given image into four corners and the central crop plus the
      flipped version of these (horizontal flipping is used by default).
      If the image is torch Tensor, it is expected
      to have [..., H, W] shape, where ... means an arbitrary number of leading dimensions
  
      .. Note::
          This transform returns a tuple of images and there may be a
          mismatch in the number of inputs and targets your ``Dataset`` returns.
  
      Args:
          img (PIL Image or Tensor): Image to be cropped.
          size (sequence or int): Desired output size of the crop. If size is an
              int instead of sequence like (h, w), a square crop (size, size) is
              made. If provided a sequence of length 1, it will be interpreted as (size[0], size[0]).
          vertical_flip (bool): Use vertical flipping instead of horizontal
  
      Returns:
          tuple: tuple (tl, tr, bl, br, center, tl_flip, tr_flip, bl_flip, br_flip, center_flip)
          Corresponding top left, top right, bottom left, bottom right and
          center crop and same for the flipped image.
      """
      if not torch.jit.is_scripting() and not torch.jit.is_tracing():
          _log_api_usage_once(ten_crop)
      if isinstance(size, numbers.Number):
          size = (int(size), int(size))
      elif isinstance(size, (tuple, list)) and len(size) == 1:
          size = (size[0], size[0])
  
      if len(size) != 2:
          raise ValueError(
              "Please provide only two dimensions (h, w) for size."
          )
  
      first_five = five_crop(img, size)
  
      if vertical_flip:
          img = vflip(img)
      else:
          img = hflip(img)
  
      second_five = five_crop(img, size)
      return first_five + second_five
  
imports: import math
  import numbers
  import sys
  import warnings
  from enum import Enum
  from typing import Any, List, Optional, Tuple, Union
  import numpy
  import torch
  from PIL import Image
  from torch import Tensor
  from ..utils import _log_api_usage_once
  from .None import _functional_pil, _functional_tensor
label_desc: Use image node_id 23 for calling a global function with example usage: ten_crop(img, size, vertical_flip) and returns: unknown