code: def GaussianAugmentationDefence(x, y, std, r):
      # 强制拷贝
      x_raw = x.copy()
      y_raw = y
  
      size = int(x_raw.shape[0] * r)
      # 随机选择指定数目的原始数据
      indices = np.random.randint(0, x_raw.shape[0], size=size)
  
      # 叠加高斯噪声
      x_gad = np.random.normal(
          x_raw[indices],
          scale=std,
          size=(size,) + x_raw[indices].shape[1:],
      )
      x_gad = np.vstack((x_raw, x_gad))
  
      y_gad = np.concatenate((y_raw, y_raw[indices]))
      return x_gad, y_gad
  
label_desc: Use image node_id 1 for calling a global function with example usage: GaussianAugmentationDefence(x, y, std, r) and returns: x_gad,  y_gad