code: def temp_ava_dataset_2_videos():
      frame_names = [f"{str(i)}.png" for i in range(90)]
      # Create csv containing 2 test frame videos.
      with tempfile.NamedTemporaryFile(
          delete=False, suffix=".csv"
      ) as frames_file:
          frames_file.write(
              "original_vido_id video_id frame_id path labels\n".encode()
          )
          # Frame video 1
          with temp_frame_video(frame_names) as (
              frame_1_video_dir,
              data_1,
          ):
              for i, frame_name in enumerate(frame_names):
                  original_video_id_1 = str(frame_1_video_dir)
                  video_id = "1"
                  frame_id = str(i)
                  path = pathlib.Path(frame_1_video_dir) / frame_name
                  label = "0"
                  frames_file.write(
                      f"{original_video_id_1} {video_id} {frame_id} {path} {label}\n".encode()
                  )
  
              # Frame video 2
              with temp_frame_video(frame_names, height=5, width=5) as (
                  frame_2_video_dir,
                  data_2,
              ):
                  for i, frame_name in enumerate(frame_names):
                      original_video_id_2 = str(frame_2_video_dir)
                      video_id = "2"
                      frame_id = str(i)
                      path = (
                          pathlib.Path(frame_2_video_dir) / frame_name
                      )
                      label = "1"
                      frames_file.write(
                          f"{original_video_id_2} {video_id} {frame_id} {path} {label}\n".encode()
                      )
  
                  frames_file.close()
                  yield frames_file.name, data_1, data_2, original_video_id_1, original_video_id_2
  
file_path: pytorchvideo/tests/test_data_ava_dataset.py
imports: import contextlib
  import pathlib
  import random
  import tempfile
  import unittest
  import torch
  from pytorchvideo.data import Ava
  from pytorchvideo.data.clip_sampling import make_clip_sampler
  from utils import temp_frame_video
label_desc: Use image node_id 1 for calling a global function with example usage: temp_ava_dataset_2_videos() without return types