code: def saturate(
      x: np.ndarray, strength: tuple, xrange: tuple = None
  ) -> np.ndarray:
      """
      Change colour saturation of image.
  
      Parameters
      ----------
      x
          Instance to be perturbed.
      strength
          Strength of saturation change. Tuple consists of (multiplier, shift) of the perturbation.
      xrange
          Tuple with min and max data range.
  
      Returns
      -------
      Perturbed instance.
      """
      x, scale_back = scale_minmax(x, xrange)
      x = sk.color.rgb2hsv(x)
      x[:, :, 1] = x[:, :, 1] * strength[0] + strength[1]
      if isinstance(xrange, tuple):
          x[:, :, 1] = np.clip(x[:, :, 1], xrange[0], xrange[1])
      x_sa = sk.color.hsv2rgb(x)
      if scale_back:
          x_sa = x_sa * (xrange[1] - xrange[0]) + xrange[0]
      if isinstance(xrange, tuple):
          return np.clip(x_sa, xrange[0], xrange[1])
      else:
          return x_sa
  
imports: import random
  from io import BytesIO
  from typing import List, Tuple, Union
  import cv2
  import numpy
  import skimage
  from alibi_detect.utils.data import Bunch
  from alibi_detect.utils.discretizer import Discretizer
  from alibi_detect.utils.distance import abdm, multidim_scaling
  from alibi_detect.utils.mapping import ohe2ord
  from PIL import Image
  from scipy.ndimage import zoom
  from scipy.ndimage.interpolation import map_coordinates
  from skimage.filters import gaussian
label_desc: Use image node_id 20 for calling a global function with example usage: saturate(x, strength, xrange) and returns: np, x_sa