Returns SplitGenerators.

def _split_generators(self, dl_manager):
    """Returns SplitGenerators."""
    paths = dl_manager.download_and_extract(_URLS)
    # Load labels from CSVs:
    def load(names):
      csv_positions = [0] * len(names)
      return functools.partial(_load_objects, [paths[name] for name in names],
                               csv_positions)
    train_objects = load(['train_human_labels', 'train_machine_labels'])
    test_objects = load(['test_human_labels', 'test_machine_labels'])
    validation_objects = load(['validation_human_labels',
                               'validation_machine_labels'])
    def load_boxes(name):
      csv_positions = [0]
      return functools.partial(_load_bboxes, paths[name], csv_positions)
    train_bbox = load_boxes('train-annotations-bbox')
    test_bbox = load_boxes('test-annotations-bbox')
    validation_bbox = load_boxes('validation-annotations-bbox')
    return [
        tfds.core.SplitGenerator(
            name=tfds.Split.TRAIN,
            num_shards=512,
            gen_kwargs=dict(archive_paths=paths['train_images'],
                            objects_getter=train_objects,
                            bboxes_getter=train_bbox,
                            prefixes='0123456789abcdef'),
        ),
        tfds.core.SplitGenerator(
            name=tfds.Split.TEST,
            num_shards=36,
            gen_kwargs=dict(archive_paths=[paths['test_images']],
                            objects_getter=test_objects,
                            bboxes_getter=test_bbox),
        ),
        tfds.core.SplitGenerator(
            name=tfds.Split.VALIDATION,
            num_shards=12,
            gen_kwargs=dict(archive_paths=[paths['validation_images']],
                            objects_getter=validation_objects,
                            bboxes_getter=validation_bbox),
        ),
    ]