code: def mmd_compute(x, y, kernel_type, gamma):
      if kernel_type == "gaussian":
          Kxx = gaussian_kernel(x, x, gamma).mean()
          Kyy = gaussian_kernel(y, y, gamma).mean()
          Kxy = gaussian_kernel(x, y, gamma).mean()
          return Kxx + Kyy - 2 * Kxy
      else:
          mean_x = x.mean(0, keepdim=True)
          mean_y = y.mean(0, keepdim=True)
          cent_x = x - mean_x
          cent_y = y - mean_y
          cova_x = (cent_x.t() @ cent_x) / (len(x) - 1)
          cova_y = (cent_y.t() @ cent_y) / (len(y) - 1)
  
          mean_diff = (mean_x - mean_y).pow(2).mean()
          cova_diff = (cova_x - cova_y).pow(2).mean()
  
          return mean_diff + cova_diff
  
label_desc: Use image node_id 3 for calling a global function with example usage: mmd_compute(x, y, kernel_type, gamma) and returns: unknown, unknown