code: def kinetics():
      return itertools.chain.from_iterable(
          [
              collect_urls(
                  datasets.Kinetics,
                  path.join(ROOT, f"Kinetics{num_classes}"),
                  frames_per_clip=1,
                  num_classes=num_classes,
                  split=split,
                  download=True,
              )
              for num_classes, split in itertools.product(
                  ("400", "600", "700"), ("train", "val")
              )
          ]
      )
  
imports: import contextlib
  import itertools
  import tempfile
  import time
  import traceback
  import unittest.mock
  import warnings
  from datetime import datetime
  from distutils import dir_util
  from os import path
  from urllib.error import HTTPError, URLError
  from urllib.parse import urlparse
  from urllib.request import Request, urlopen
  import pytest
  from torchvision import datasets
  from torchvision.datasets.utils import _get_redirect_url, USER_AGENT
label_desc: Use image node_id 31 for calling a global function with example usage: kinetics() and returns: itertools