code: def gm_blur_kernel(mean, cov, size=15):
      center = size / 2.0 + 0.5
      k = np.zeros([size, size])
      for y in range(size):
          for x in range(size):
              cy = y - center + 1
              cx = x - center + 1
              k[y, x] = ss.multivariate_normal.pdf(
                  [cx, cy], mean=mean, cov=cov
              )
  
      k = k / np.sum(k)
      return k
  
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 4 for calling a global function with example usage: gm_blur_kernel(mean, cov, size) and returns: k