def filter_paired_dataset_indices_by_size(src_sizes, tgt_sizes, indices, max_sizes):
    """Filter a list of sample indices. Remove those that are longer
        than specified in max_sizes.

    Args:
        indices (np.array): original array of sample indices
        max_sizes (int or list[int] or tuple[int]): max sample size,
            can be defined separately for src and tgt (then list or tuple)

    Returns:
        np.array: filtered sample array
        list: list of removed indices
    """
    if max_sizes is None:
        return indices, []
    if type(max_sizes) in (int, float):
        max_src_size, max_tgt_size = max_sizes, max_sizes
    else:
        max_src_size, max_tgt_size = max_sizes
    if tgt_sizes is None:
        ignored = indices[src_sizes[indices] > max_src_size]
    else:
        ignored = indices[
            (src_sizes[indices] > max_src_size) | (tgt_sizes[indices] > max_tgt_size)
        ]
    if len(ignored) > 0:
        if tgt_sizes is None:
            indices = indices[src_sizes[indices] <= max_src_size]
        else:
            indices = indices[
                (src_sizes[indices] <= max_src_size)
                & (tgt_sizes[indices] <= max_tgt_size)
            ]
    return indices, ignored.tolist()
Filter a list of sample indices. Remove those that are longer
        than specified in max_sizes.

    Args:
        indices (np.array): original array of sample indices
        max_sizes (int or list[int] or tuple[int]): max sample size,
            can be defined separately for src and tgt (then list or tuple)

    Returns:
        np.array: filtered sample array
        list: list of removed indices
    
structured_prompting/fairseq-version/fairseq/fairseq/data/data_utils.py