How to use the tfrecord.iterator_utils.sample_iterators function in tfrecord

values ("byte", "float", or "int") correspond to the data type.
        If dtypes are provided, then they are verified against the
        inferred type for compatibility purposes. If None (default),
        then all features contained in the file are extracted.

    Returns:
    --------
    it: iterator
        A repeating iterator that generates batches of data.
    """
    loaders = [functools.partial(tfrecord_loader, data_path=data_pattern.format(split),
                                 index_path=index_pattern.format(split) \
                                     if index_pattern is not None else None,
                                 description=description)
               for split in splits.keys()]
    return iterator_utils.sample_iterators(loaders, list(splits.values()))