code: def test_image_pipeline(dev, layout_batch_size):
      layout, batch_size = layout_batch_size
      num_iters = 2
  
      pipe = images_pipeline(
          num_threads=4,
          device_id=0,
          batch_size=batch_size,
          layout=layout,
          dev=dev,
      )
      pipe.build()
  
      for _ in range(num_iters):
          equalized, imgs = pipe.run()
          if dev == "gpu":
              imgs = imgs.as_cpu()
              equalized = equalized.as_cpu()
          equalized = [np.array(img) for img in equalized]
          imgs = [np.array(img) for img in imgs]
          assert len(equalized) == len(imgs)
          baseline = [equalize_cv_baseline(img, layout) for img in imgs]
          check_batch(equalized, baseline, max_allowed_error=1)
  
file_path: DALI/dali/test/python/operator_2/test_equalize.py
imports: import os
  import math
  import itertools
  import cv2
  import numpy
  from nvidia.dali import pipeline_def, fn, types
  from test_utils import get_dali_extra_path, check_batch
  from nose2.tools import params
label_desc: Use image node_id 3 for calling a global function with example usage: test_image_pipeline(dev, layout_batch_size) without return types