code: def _test_augmenter(
      cls, augmenter_name, func_expected, dependent_on_seed
  ):
      # this test verifies:
      # - called function seems to be the expected function
      # - images produced by augmenter match images produced by function
      # - a different seed (and sometimes severity) will lead to a
      #   different image
      # - augmenter can be pickled
      severity = 5
      aug_cls = getattr(iaa.imgcorruptlike, augmenter_name)
      image = (
          np.mod(np.arange(32 * 32 * 3), 256)
          .reshape((32, 32, 3))
          .astype(np.uint8)
      )
  
      with iap.no_prefetching():
          rng = iarandom.RNG(1)
          # Replay sampling of severities.
          # Even for deterministic values this is required as currently
          # there is an advance() at the end of each draw_samples().
          _ = iap.Deterministic(1).draw_samples((1,), rng)
  
          # As for the functions above, we can't just change the seed value
          # to get different augmentations as many functions are dependend
          # only on the severity. So we change only for some functions only
          # the seed and for the others severity+seed.
          image_aug1 = aug_cls(severity=severity, seed=1)(image=image)
          image_aug2 = aug_cls(severity=severity, seed=1)(image=image)
          if dependent_on_seed:
              image_aug3 = aug_cls(severity=severity, seed=2)(
                  image=image
              )
          else:
              image_aug3 = aug_cls(severity=severity - 1, seed=2)(
                  image=image
              )
          image_aug_exp = func_expected(
              image, severity=severity, seed=rng.generate_seed_()
          )
  
      assert aug_cls(severity=severity).func is func_expected
      assert np.array_equal(image_aug1, image_aug_exp)
      assert np.array_equal(image_aug2, image_aug_exp)
      assert not np.array_equal(image_aug3, image_aug2)
  
      # pickling test
      aug = aug_cls(severity=(1, 5))
      runtest_pickleable_uint8_img(aug, shape=(32, 32, 3))
  
imports: from __future__ import print_function, division, absolute_import
  import sys
  import functools
  import numpy
  import imgaug
  from imgaug import augmenters
  from imgaug import random
  from imgaug import parameters
  from imgaug.testutils import runtest_pickleable_uint8_img
label_desc: Use image node_id 1 for calling the TestAugmenters obj's underlying member method code with example usage: obj._test_augmenter(cls, augmenter_name, func_expected, dependent_on_seed) without return types