code: def compare_video_resize_pipelines(
      pipeline, gt_pipeline, batch_size, video_length
  ):
      global_sample_id = 0
      (batch_gpu,) = pipeline.run()
      batch = batch_gpu.as_cpu()
  
      for sample_id in range(batch_size):
          global_sample_id = global_sample_id + 1
          sample = batch.at(sample_id)
          for frame_id in range(video_length):
              frame = sample[frame_id]
              gt_frame = gt_pipeline.run()[0].as_cpu().as_array()[0]
              if gt_frame.shape == frame.shape:
                  assert (
                      gt_frame == frame
                  ).all(), "Images are not equal"
              else:
                  assert (
                      gt_frame.shape == frame.shape
                  ), f"Shapes are not equal: {gt_frame.shape} != {frame.shape}"
  
file_path: DALI/dali/test/python/test_video_reader_resize.py
imports: import gc
  import numpy
  import nvidia.dali
  import nvidia.dali.types
label_desc: Use image node_id 5 for calling a global function with example usage: compare_video_resize_pipelines(pipeline, gt_pipeline, batch_size, video_length) without return types