code: def test_stress_test_read_video_from_file(self, test_video):
      pytest.skip(
          "This stress test will iteratively decode the same set of videos."
          "It helps to detect memory leak but it takes lots of time to run."
          "By default, it is disabled"
      )
      num_iter = 10000
      # video related
      width, height, min_dimension, max_dimension = 0, 0, 0, 0
      video_start_pts, video_end_pts = 0, -1
      video_timebase_num, video_timebase_den = 0, 1
      # audio related
      samples, channels = 0, 0
      audio_start_pts, audio_end_pts = 0, -1
      audio_timebase_num, audio_timebase_den = 0, 1
  
      for _i in range(num_iter):
          full_path = os.path.join(VIDEO_DIR, test_video)
  
          # pass 1: decode all frames using new decoder
          torch.ops.video_reader.read_video_from_file(
              full_path,
              SEEK_FRAME_MARGIN,
              0,  # getPtsOnly
              1,  # readVideoStream
              width,
              height,
              min_dimension,
              max_dimension,
              video_start_pts,
              video_end_pts,
              video_timebase_num,
              video_timebase_den,
              1,  # readAudioStream
              samples,
              channels,
              audio_start_pts,
              audio_end_pts,
              audio_timebase_num,
              audio_timebase_den,
          )
  
imports: import collections
  import math
  import os
  from fractions import Fraction
  import numpy
  import pytest
  import torch
  import torchvision.io
  from common_utils import assert_equal
  from numpy.random import randint
  from pytest import approx
  from torchvision import set_video_backend
  from torchvision.io import _HAS_VIDEO_OPT
label_desc: Use image node_id 5 for calling the TestVideoReader obj's underlying member method code with example usage: obj.test_stress_test_read_video_from_file(test_video) without return types