def METHOD_NAME(readers, use_pipe=True, queue_size=1000, pipe_size=10):
    """
    multiprocess_reader use python multi process to read data from readers
    and then use multiprocess.Queue or multiprocess.Pipe to merge all
    data. The process number is equal to the number of input readers, each
    process call one reader.
    Multiprocess.Queue require the rw access right to /dev/shm, some
    platform does not support.
    you need to create multiple readers first, these readers should be independent
    to each other so that each process can work independently.
    An example:
    .. code-block:: python
        reader0 = reader(["file01", "file02"])
        reader1 = reader(["file11", "file12"])
        reader1 = reader(["file21", "file22"])
        reader = multiprocess_reader([reader0, reader1, reader2],
            queue_size=100, use_pipe=False)
    """
    assert type(readers) is list and len(readers) > 0
    def _read_into_queue(reader, queue):
        """read_into_queue"""
        for sample in reader():
            if sample is None:
                raise ValueError("sample has None")
            queue.put(serialize_data(sample))
        queue.put(serialize_data(None))
    def queue_reader():
        """queue_reader"""
        queues = []
        for reader in readers:
            queue = multiprocessing.Queue(queue_size)
            queues.append(queue)
            p = multiprocessing.Process(
                target=_read_into_queue, args=(reader, queue))
            p.start()
        reader_num = len(readers)
        alive_queue_indices = [i for i in range(reader_num)]
        while len(alive_queue_indices) > 0:
            for alive_queue_index in [i for i in alive_queue_indices]:
                sample = deserialize_data(queues[alive_queue_index].get())
                if sample is None:
                    alive_queue_indices.remove(alive_queue_index)
                else:
                    yield sample
    def _read_into_pipe(reader, conn, max_pipe_size):
        """read_into_pipe"""
        for sample in reader():
            if sample is None:
                raise ValueError("sample has None!")
            conn.send(serialize_data(sample))
        conn.send(serialize_data(None))
        conn.close()
    def pipe_reader():
        """pipe_reader"""
        conns = []
        for reader in readers:
            parent_conn, child_conn = multiprocessing.Pipe()
            conns.append(parent_conn)
            p = multiprocessing.Process(
                target=_read_into_pipe, args=(reader, child_conn, pipe_size))
            p.start()
        reader_num = len(readers)
        conn_to_remove = []
        finish_flag = np.zeros(len(conns), dtype="int32")
        alive_conn_indices = [i for i in range(reader_num)]
        while len(alive_conn_indices) > 0:
            for alive_conn_index in [i for i in alive_conn_indices]:
                sample = deserialize_data(conns[alive_conn_index].recv())
                if sample is None:
                    conns[alive_conn_index].close()
                    alive_conn_indices.remove(alive_conn_index)
                else:
                    yield sample
    if use_pipe:
        return pipe_reader
    else:
        return queue_reader