code: def temp_charades_dataset():
      # Create csv containing 2 test frame videos.
      with tempfile.NamedTemporaryFile(
          delete=False, suffix=".csv"
      ) as f:
          f.write(
              "original_vido_id video_id frame_id path labels\n".encode()
          )
  
          with temp_frame_video_dataset() as (video_frames, _):
              for (
                  original_video_id,
                  video_id,
                  frame_id,
                  path,
                  label,
                  _,
              ) in video_frames:
                  f.write(
                      f"{original_video_id} {video_id} {frame_id} {path} {label}\n".encode()
                  )
  
              f.close()
              yield f.name, video_frames[0][-1], video_frames[1][-1]
  
file_path: pytorchvideo/tests/test_data_charades_dataset.py
imports: import contextlib
  import pathlib
  import tempfile
  import unittest
  from pytorchvideo.data import Charades
  from pytorchvideo.data.clip_sampling import make_clip_sampler
  from torch.utils.data import SequentialSampler
  from utils import temp_frame_video, temp_frame_video_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: temp_charades_dataset() without return types