code: def test_augmenters(self):
      # ColorNormalizeAug
      mean = np.random.rand(3) * 255
      std = np.random.rand(3) + 1
      width = np.random.randint(100, 500)
      height = np.random.randint(100, 500)
      src = np.random.rand(height, width, 3) * 255.0
      # We test numpy and mxnet NDArray inputs
      color_norm_aug = mx.image.ColorNormalizeAug(
          mean=mx.nd.array(mean), std=std
      )
      out_image = color_norm_aug(mx.nd.array(src))
      assert_almost_equal(
          out_image.asnumpy(), (src - mean) / std, atol=1e-3
      )
  
      # only test if all augmenters will work
      # TODO(Joshua Zhang): verify the augmenter outputs
      im_list = [[0, x] for x in self.IMAGES]
      test_iter = mx.image.ImageIter(
          2,
          (3, 224, 224),
          label_width=1,
          imglist=im_list,
          resize=640,
          rand_crop=True,
          rand_resize=True,
          rand_mirror=True,
          mean=True,
          std=np.array([1.1, 1.03, 1.05]),
          brightness=0.1,
          contrast=0.1,
          saturation=0.1,
          hue=0.1,
          pca_noise=0.1,
          rand_gray=0.2,
          inter_method=10,
          path_root=self.IMAGES_DIR,
          shuffle=True,
      )
      for _ in test_iter:
          pass
  
imports: import os
  import mxnet
  import numpy
  import scipy.ndimage
  from mxnet.test_utils import *
  from common import xfail_when_nonstandard_decimal_separator
  import shutil
  import tempfile
  import unittest
  import pytest
label_desc: Use image node_id 15 for calling the TestImage obj's underlying member method code with example usage: obj.test_augmenters() without return types