code: def gaussian_kernel(n, std):
      gaussian_1d = signal.gaussian(n, std)
      gaussian_2d = np.outer(gaussian_1d, gaussian_1d)
      gaussian_3d = np.outer(gaussian_2d, gaussian_1d)
      gaussian_3d = gaussian_3d.reshape(n, n, n)
      gaussian_3d = np.cbrt(gaussian_3d)
      gaussian_3d /= gaussian_3d.max()
      return gaussian_3d
  
file_path: tinygrad/examples/mlperf/helpers.py
imports: from collections import OrderedDict
  import unicodedata
  import numpy
  from scipy import signal
label_desc: Use image node_id 1 for calling a global function with example usage: gaussian_kernel(n, std) and returns: gaussian_3d