code: def mock_encoded_video_dataset_folder(tmpdir):
      """Creates a temporary mock encoded video directory tree with 2 videos labeled 1, 2.
  
      Returns a directory that to this mock encoded video dataset and the video duration in seconds.
  
      """
      num_frames = 10
      fps = 5
  
      tmp_dir = Path(tmpdir)
      os.makedirs(str(tmp_dir / "c1"))
      os.makedirs(str(tmp_dir / "c2"))
  
      with temp_encoded_video(
          num_frames=num_frames, fps=fps, directory=str(tmp_dir / "c1")
      ), temp_encoded_video(
          num_frames=num_frames, fps=fps, directory=str(tmp_dir / "c2")
      ):
          video_duration = num_frames / fps
          yield str(tmp_dir), video_duration
  
imports: import contextlib
  import os
  import tempfile
  from pathlib import Path
  from typing import Any
  import flash
  import pytest
  import torch
  from flash.core.data.io.input import DataKeys
  from flash.core.utilities.imports import _FIFTYONE_AVAILABLE, _TOPIC_VIDEO_AVAILABLE
  from flash.video import VideoClassificationData, VideoClassifier
  from pandas import DataFrame
  from torch import Tensor
  from torch.utils.data import SequentialSampler
  from tests.helpers.task_tester import TaskTester
  from tests.video.classification.test_data import create_dummy_video_frames, temp_encoded_tensors
label_desc: Use image node_id 4 for calling a global function with example usage: mock_encoded_video_dataset_folder(tmpdir) without return types