code: def gaussian2D(shape, sigma_x=1, sigma_y=1):
      m, n = [(ss - 1.0) / 2.0 for ss in shape]
      y, x = np.ogrid[-m : m + 1, -n : n + 1]
  
      h = np.exp(
          -(
              x * x / (2 * sigma_x * sigma_x)
              + y * y / (2 * sigma_y * sigma_y)
          )
      )
      h[h < np.finfo(h.dtype).eps * h.max()] = 0
      return h
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import random
  import math
  import cv2
label_desc: Use image node_id 19 for calling a global function with example usage: gaussian2D(shape, sigma_x, sigma_y) and returns: h