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):
                feat_file = os.path.join(tmpdir, f"feat_{i}.pt")
                torch.save(torch.randn(80, 5), feat_file)
                entry = {'feature_file': feat_file, 'duration': 100000, 'label': '0'}
                fp.write(json.dumps(entry) + '\n')
        dataset = FeatureToLabelDataset(manifest_filepath=manifest_path, labels=self.unique_labels_in_seq)
        correct_label = torch.tensor(self.unique_labels_in_seq.index('0'))
        correct_label_length = torch.tensor(1)
        assert dataset[0][0].shape == (80, 5)
        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