How to use the squad.utils.get_best_span function in squad

template = env.get_template(args.template_name)

    data_path = os.path.join(data_dir, "data_{}.json".format(data_type))
    shared_path = os.path.join(data_dir, "shared_{}.json".format(data_type))
    print("loading {}".format(data_path))
    data = json.load(open(data_path, 'r'))
    print("loading {}".format(shared_path))
    shared = json.load(open(shared_path, 'r'))

    rows = []
    for i, (idx, yi, ypi, yp2i) in tqdm(enumerate(zip(*[eval_[key] for key in ('idxs', 'y', 'yp', 'yp2')])), total=len(eval_['idxs'])):
        id_, q, rx, answers = (data[key][idx] for key in ('ids', 'q', '*x', 'answerss'))
        x = shared['x'][rx[0]][rx[1]]
        ques = [" ".join(q)]
        para = [[word for word in sent] for sent in x]
        span = get_best_span(ypi, yp2i)
        ap = get_segment(para, span)
        score = "{:.3f}".format(ypi[span[0][0]][span[0][1]] * yp2i[span[1][0]][span[1][1]-1])

        row = {
            'id': id_,
            'title': "Hello world!",
            'ques': ques,
            'para': para,
            'y': yi[0][0],
            'y2': yi[0][1],
            'yp': ypi,
            'yp2': yp2i,
            'a': answers,
            'ap': ap,
            'score': score
               }

def ensemble1(context, wordss, y1_list, y2_list):
    """

    :param context: Original context
    :param wordss: tokenized words (nested 2D list)
    :param y1_list: list of start index probs (each element corresponds to probs form single model)
    :param y2_list: list of stop index probs
    :return:
    """
    sum_y1 = combine_y_list(y1_list)
    sum_y2 = combine_y_list(y2_list)
    span, score = get_best_span(sum_y1, sum_y2)
    return get_phrase(context, wordss, span)

new_yi.append((new_start, new_stop))
                new_y.append(new_yi)
            y = new_y
        if self.config.single:
            new_y = []
            for yi in y:
                new_yi = []
                for start, stop in yi:
                    new_start = 0, start[1]
                    new_stop = 0, stop[1]
                    new_yi.append((new_start, new_stop))
                new_y.append(new_yi)
            y = new_y

        yp, yp2, p = yp[:data_set.num_examples], yp2[:data_set.num_examples], p[:data_set.num_examples]
        spans, scores = zip(*[get_best_span(ypi, yp2i) for ypi, yp2i in zip(yp, yp2)])

        def _get(xi, span):
            if len(xi) <= span[0][0]:
                return [""]
            if len(xi[span[0][0]]) <= span[1][1]:
                return [""]
            return xi[span[0][0]][span[0][1]:span[1][1]]

        def _get2(context, xi, span):
            if len(xi) <= span[0][0]:
                return ""
            if len(xi[span[0][0]]) <= span[1][1]:
                return ""
            return get_phrase(context, xi, span)
        id2answer_dict = {id_: _get2(context, xi, span)
                          for id_, xi, span, context in zip(data_set.data['ids'], data_set.data['x'], spans, data_set.data['p'])}

def ensemble3(context, wordss, y1_list, y2_list):
    d = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        phrase = get_phrase(context, wordss, span)
        d[phrase] += score
    return max(d.items(), key=lambda pair: pair[1])[0]

def ensemble3(context, wordss, y1_list, y2_list):
    d = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        phrase = get_phrase(context, wordss, span)
        d[phrase] += score
    return max(d.items(), key=lambda pair: pair[1])[0]

template = env.get_template(args.template_name)

    data_path = os.path.join(data_dir, "data_{}.json".format(data_type))
    shared_path = os.path.join(data_dir, "shared_{}.json".format(data_type))
    print("loading {}".format(data_path))
    data = json.load(open(data_path, 'r'))
    print("loading {}".format(shared_path))
    shared = json.load(open(shared_path, 'r'))

    rows = []
    for i, (idx, yi, ypi, yp2i) in tqdm(enumerate(zip(*[eval_[key] for key in ('idxs', 'y', 'yp', 'yp2')])), total=len(eval_['idxs'])):
        id_, q, rx, answers = (data[key][idx] for key in ('ids', 'q', '*x', 'answerss'))
        x = shared['x'][rx[0]][rx[1]]
        ques = [" ".join(q)]
        para = [[word for word in sent] for sent in x]
        span = get_best_span(ypi, yp2i)
        ap = get_segment(para, span)
        score = "{:.3f}".format(ypi[span[0][0]][span[0][1]] * yp2i[span[1][0]][span[1][1]-1])

        row = {
            'id': id_,
            'title': "Hello world!",
            'ques': ques,
            'para': para,
            'y': yi[0][0],
            'y2': yi[0][1],
            'yp': ypi,
            'yp2': yp2i,
            'a': answers,
            'ap': ap,
            'score': score
               }

def ensemble2(context, wordss, y1_list, y2_list):
    start_dict = defaultdict(float)
    stop_dict = defaultdict(float)
    for y1, y2 in zip(y1_list, y2_list):
        span, score = get_best_span(y1, y2)
        start_dict[span[0]] += y1[span[0][0]][span[0][1]]
        stop_dict[span[1]] += y2[span[1][0]][span[1][1]]
    start = max(start_dict.items(), key=lambda pair: pair[1])[0]
    stop = max(stop_dict.items(), key=lambda pair: pair[1])[0]
    best_span = (start, stop)
    return get_phrase(context, wordss, best_span)