code: def center_crop(
      image: Tensor, target_size: Optional[Tuple] = None
  ) -> Tensor:
      r"""Computes the centre crop of an image using `target_size`
  
      Args:
          image (Tensor): Valid image Tensor
          target_size (tuple): Size of the centre crop. Must be in the format `(width,height)`
  
      Returns:
          Cropped Centre (Tensor)
  
      Examples::
  
          >> tens = caer.data.bear() # Standard 640x427 image
          >> cropped = caer.center_crop(tens, target_size=(200,200))
          >> cropped.shape
          (200,200,3)
  
      """
      return _compute_centre_crop(image, target_size)
  
imports: import numpy
  import cv2
  import random
  import collections
  from ..coreten import Tensor, to_tensor
  from .._internal import _check_target_size
  from ..globals import INTER_AREA, INTER_CUBIC, INTER_NEAREST, INTER_LINEAR
  from ..annotations import Union, Tuple, Optional
label_desc: Use image node_id 14 for calling a global function with example usage: center_crop(image, target_size) and returns: _compute_centre_crop