Function work

evaluation/eval.py:362–414

(model_out)

    bp = 0
    b_div = 0
    def work(model_out):
        global ask, tell, lev_info, auv, lock, logger, entities
        global total_informational_div, informational, support_info
        global br, bf, bp, b_div
        if isinstance(model_out['model'], list):
            model_out['model'] = model_out['model'][0]
        r, p, f = score([
            model_out["model"],
        ], [model_out['src']['conversation'][-1]['doctor']], lang='zh')
        br += r[0]
        bf += p[0]
        bp += f[0]
        b_div += 1
        logger.info(model_out)
        if is_ask(model_out["model"]):
            model_entities = generate_entities(model_out["model"])
            actual_resp = model_out['src']['conversation'][-1]['doctor']
            actual_entities = generate_entities(actual_resp)
            t_auv = get_auv(model_out, model_entities)
            lev_d = Levenshtein.ratio(
                flatten_medical_ask_content(actual_entities),
                flatten_medical_ask_content(model_entities),
            )
            entities.append(
                (actual_entities, model_entities)
            )
            if True:
                ask += 1
                lev_info.append(lev_d)
                auv.append(
                    t_auv
                )
        else:
            tell += 1
            actual_resp = model_out['src']['conversation'][-1]['doctor']
            is_f = False
            if get_is_informational(
                model_out['src']['conversation'][-1]['patient'], 
                model_out["model"], 
                actual_resp, 
                model_out['src']['conversation'][:-1]):
                informational += 1
                is_f = True
            total_informational_div += 1
            if is_f:
                if not hallucinate(
                    model_out['src']['conversation'][-1]['patient'], 
                    model_out["model"], 
                    actual_resp, 
                    model_out['src']['conversation'][:-1]):
                    support_info.append(1)
                else:
                    support_info.append(0)
    futures = []
    for i in tqdm(data[:]):
        work(i)