How to use the ivis.data.knn.KNN_Worker function in ivis

n_dims = X.shape[1]

    chunk_size = X.shape[0] // cpu_count()
    remainder = (X.shape[0] % cpu_count()) > 0
    process_pool = []
    results_queue = Queue()

    # Split up the indices and assign processes for each chunk
    i = 0
    while (i + chunk_size) <= X.shape[0]:
        process_pool.append(KNN_Worker(index_filepath, k, search_k, n_dims,
                                       (i, i+chunk_size), results_queue))
        i += chunk_size
    if remainder:
        process_pool.append(KNN_Worker(index_filepath, k, search_k, n_dims,
                                       (i, X.shape[0]), results_queue))

    try:
        for process in process_pool:
            process.start()

        # Read from queue constantly to prevent it from becoming full
        with tqdm(total=X.shape[0], disable=verbose < 1) as pbar:
            neighbour_list = []
            neighbour_list_length = len(neighbour_list)
            while any(process.is_alive() for process in process_pool):
                while not results_queue.empty():
                    neighbour_list.append(results_queue.get())
                progress = len(neighbour_list) - neighbour_list_length
                pbar.update(progress)
                neighbour_list_length = len(neighbour_list)

def __init__(self, index_filepath, k, search_k, n_dims,
                 data_indices, results_queue):
        self.index_filepath = index_filepath
        self.k = k
        self.n_dims = n_dims
        self.search_k = search_k
        self.data_indices = data_indices
        self.results_queue = results_queue
        super(KNN_Worker, self).__init__()