code: def fspecial_laplacian(alpha):
      alpha = max([0, min([alpha, 1])])
      h1 = alpha / (alpha + 1)
      h2 = (1 - alpha) / (alpha + 1)
      h = [[h1, h2, h1], [h2, -4 / (alpha + 1), h2], [h1, h2, h1]]
      h = np.array(h)
      return h
  
imports: import random
  from functools import partial
  import albumentations
  import cv2
  import ldm.modules.image_degradation.utils_image
  import numpy
  import scipy
  import scipy.stats
  import torch
  from scipy import ndimage
  from scipy.interpolate import interp2d
  from scipy.linalg import orth
label_desc: Use image node_id 9 for calling a global function with example usage: fspecial_laplacian(alpha) and returns: h