def _embedding_reader(filename, input_queue, block_size=1000):
    """ Process that reads the word embeddings from a file.

    Parameters
    ----------
    filename: str
        File of trained embedding vectors.
    input_queue: Queue
        Queue to store jobs in.
    block_size: int
        Number of lines for each job.
    """
    with open(filename, 'r', encoding='utf-8', newline='\n') as f:
        f.readline()
        i_line = 0
        buffer = []
        for line in f:
            i_line += 1
            buffer.append(line)
            if i_line == block_size:
                input_queue.put(buffer)
                i_line = 0
                buffer = []
        if i_line > 0:
            input_queue.put(buffer)
    input_queue.put('DONE')
