code: def run_for_params(batch_size, video_reader_params, resize_params):
      pipeline = video_reader_resize_pipeline(
          batch_size, video_reader_params, resize_params
      )
  
      gt_pipeline = ground_truth_pipeline(
          batch_size, video_reader_params, resize_params
      )
  
      compare_video_resize_pipelines(
          pipeline,
          gt_pipeline,
          batch_size,
          video_reader_params["sequence_length"],
      )
  
      # The intermediate pipeline from ground_truth_pipeline gets entangled in cell objects
      # and is not automatically destroyed. The pipeline outputs are kept alive,
      # effectively leaking large amounts of GPU memory.
      gc.collect()
  
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 6 for calling a global function with example usage: run_for_params(batch_size, video_reader_params, resize_params) without return types