code: def mock_json_annotations():
      with temp_frame_video_dataset() as (_, videos):
          label_videos = []
          json_dict = {}
          for video in videos:
              label_videos.append((video[-3], video[-2]))
              name = str(video[0])
              json_dict[name] = {
                  "benchmarks": {
                      "forecasting_hands_objects": [
                          {
                              "critical_frame_selection_parent_start_sec": 0.001,
                              "critical_frame_selection_parent_end_sec": 0.012,
                              "taxonomy": {
                                  "noun": video[-3],
                                  "verb": video[-3],
                                  "noun_unsure": False,
                                  "verb_unsure": False,
                              },
                          },
                          {
                              "critical_frame_selection_parent_start_sec": 0.01,
                              "critical_frame_selection_parent_end_sec": 0.05,
                              "taxonomy": {
                                  "noun": video[-3],
                                  "verb": video[-3],
                                  "noun_unsure": False,
                                  "verb_unsure": False,
                              },
                          },
                      ]
                  }
              }
  
          with tempfile.NamedTemporaryFile(
              delete=False, suffix=".json", mode="wt"
          ) as f:
              json.dump(json_dict, f)
              f.close()
  
          min_duration = min(videos[0][-1], videos[1][-1])
          yield f.name, label_videos, min_duration
  
file_path: pytorchvideo/tests/test_data_json_dataset.py
imports: import contextlib
  import json
  import tempfile
  import unittest
  from pytorchvideo.data import json_dataset
  from pytorchvideo.data.clip_sampling import make_clip_sampler
  from pytorchvideo.data.labeled_video_dataset import LabeledVideoDataset
  from utils import temp_frame_video_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: mock_json_annotations() without return types