def METHOD_NAME(self):
    with tempfile.TemporaryDirectory() as tmpdir:
        manifest_path = os.path.join(tmpdir, 'manifest_input.json')
        with open(manifest_path, 'w', encoding='utf-8') as fp:
            for i in range(2):
                audio_file = os.path.join(tmpdir, f"audio_{i}.wav")
                data = np.random.normal(0, 1, 16000 * 10)
                sf.write(audio_file, data, 16000)
                entry = {'audio_filepath': audio_file, 'duration': 10, 'label': '0 1 0 1'}
                fp.write(json.dumps(entry) + '\n')
        dataset = AudioToMultiLabelDataset(manifest_filepath=manifest_path, sample_rate=16000, labels=['0', '1'])
        correct_label = torch.tensor([0, 1, 0, 1])
        correct_label_length = torch.tensor(4)
        assert dataset[0][0].shape == torch.tensor([0.1] * 160000).shape
        assert torch.equal(dataset[0][2], correct_label)
        assert torch.equal(dataset[0][3], correct_label_length)
        count = 0
        for _ in dataset:
            count += 1
        assert count == 2