| import json | |
| import argparse | |
| from nltk.translate.bleu_score import sentence_bleu | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument("--category", required=True, type=str, choices=["chemistry", "physics"]) | |
| parser.add_argument("--file", required=True, type=str) | |
| args = parser.parse_args() | |
| with open(args.file, 'r') as reader: | |
| data = json.load(reader) | |
| def extract_float(pred_str): | |
| flag = False | |
| answer_str = "" | |
| for s in pred_str: | |
| if (s >= "0" and s <= "9") or s == ".": | |
| answer_str += s | |
| if flag == False: | |
| flag = True | |
| else: | |
| if flag == True: | |
| break | |
| if len(answer_str) == 0 or answer_str == ".": | |
| return 0 | |
| if answer_str[-1] == ".": | |
| answer_str = answer_str[:-1] | |
| return float(answer_str) | |
| def split_IUPAC_name(name_str): | |
| special_strs = [",", "[", "]", "-", "(", ")"] | |
| name_list = [name_str] | |
| for special_str in special_strs: | |
| new_name_list = [] | |
| for name in name_list: | |
| name_split = name.split(special_str) | |
| name_split = [s for s in name_split if len(s) != 0] | |
| new_name_list += name_split | |
| name_list = new_name_list.copy() | |
| return name_list | |
| if args.category == "chemistry": | |
| bleu_scores = [] | |
| mse_scores = [] | |
| acc_cnt = 0 | |
| for d in data: | |
| if f"{d['answer'][0]}".lower() in d["pred"]: | |
| acc_cnt += 1 | |
| if "What is the SMILES expression of " in d["question"]: | |
| answer = [a for a in d["answer"][0].lower()] | |
| pred_split = d["pred"].split(" ") | |
| max_bleu = 0 | |
| for pred in pred_split: | |
| pred = [a for a in pred.lower()] | |
| reference = [answer] | |
| score = sentence_bleu(reference, pred, weights=(0.25, 0.25, 0.25, 0.25)) | |
| if score > max_bleu: | |
| max_bleu = score | |
| bleu_scores.append(max_bleu) | |
| elif "What is the molecular formula of" in d["question"]: | |
| answer = [a for a in d["answer"][0].lower()] | |
| pred_split = d["pred"].split(" ") | |
| max_bleu = 0 | |
| for pred in pred_split: | |
| pred = [a for a in pred.lower()] | |
| reference = [answer] | |
| score = sentence_bleu(reference, pred, weights=(0.25, 0.25, 0.25, 0.25)) | |
| if score > max_bleu: | |
| max_bleu = score | |
| bleu_scores.append(max_bleu) | |
| elif "What is the molecular weight of " in d["question"]: | |
| answer = float(d["answer"][0]) | |
| min_mse = 1e10 | |
| pred_split = d["pred"].split(" ") | |
| for pred in pred_split: | |
| pred = extract_float(pred) | |
| if pred == 0: | |
| continue | |
| mse = (pred - answer) ** 2 | |
| if mse < min_mse: | |
| min_mse = mse | |
| if min_mse != 1e10: | |
| mse_scores.append(min_mse) | |
| elif "How many atoms are there in" in d["question"]: | |
| answer = float(d["answer"][0]) | |
| min_mse = 1e10 | |
| pred_split = d["pred"].split(" ") | |
| for pred in pred_split: | |
| pred = extract_float(pred) | |
| if pred == 0: | |
| continue | |
| mse = (pred - answer) ** 2 | |
| if mse < min_mse: | |
| min_mse = mse | |
| if min_mse != 1e10: | |
| mse_scores.append(min_mse) | |
| elif "What is the name of" in d["question"]: | |
| answer = split_IUPAC_name(d["answer"][0].strip().lower()) | |
| pred_split = d["pred"].split(" ") | |
| max_bleu = 0 | |
| for pred in pred_split: | |
| pred = split_IUPAC_name(pred.strip().lower()) | |
| reference = [answer] | |
| score = sentence_bleu(reference, pred, weights=(0.25, 0.25, 0.25, 0.25)) | |
| if score > max_bleu: | |
| max_bleu = score | |
| bleu_scores.append(max_bleu) | |
| print("blue: ", sum(bleu_scores) / len(bleu_scores)) | |
| print("mse: ", sum(mse_scores) / len(mse_scores)) | |
| print("EM: ", acc_cnt / len(data)) | |
| else: | |
| acc_cnt = 0 | |
| for d in data: | |
| if len(d["pred"]) == 0: | |
| continue | |
| if d["answer"][0].lower() == d["pred"][0].lower(): | |
| acc_cnt += 1 | |
| print(acc_cnt/len(data)) | |