code: def test_multiple_clips_per_video_works(self):
      with temp_charades_dataset() as (filename, video_1, video_2):
          clip_sampler = make_clip_sampler(
              "uniform",
              0.033,  # Expects each clip to have 1 frame each.
          )
          dataset = Charades(
              filename,
              clip_sampler=clip_sampler,
              video_sampler=SequentialSampler,
          )
  
          expected = [
              ([[0]], video_1[:, 0:1]),
              ([[0]], video_1[:, 1:2]),
              ([[0]], video_1[:, 2:3]),
              ([[1]], video_2[:, 0:1]),
              ([[1]], video_2[:, 1:2]),
              ([[1]], video_2[:, 2:3]),
          ]
          for sample, expected_sample in zip(dataset, expected):
              self.assertEqual(sample["label"], expected_sample[0])
              self.assertTrue(sample["video"].equal(expected_sample[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 2 for calling the TestCharadesDataset obj's underlying member method code with example usage: obj.test_multiple_clips_per_video_works() without return types