from commonsenseConstraint import evaluation as commonsense_eval from hardConstraint import evaluation as hard_eval import json from tqdm import tqdm from datasets import load_dataset def load_line_json_data(filename): data = [] with open(filename, 'r', encoding='utf-8') as f: for line in f.read().strip().split('\n'): unit = json.loads(line) data.append(unit) return data def count_true_false(data): """Count the number of true and false values in a list.""" true_count = data.count(True) false_count = data.count(False) return true_count, false_count def statistics(commonsense_statistic): """Generate statistics for each level and day in the given data with a different structure.""" result = {level: {day: {} for day in commonsense_statistic[level]} for level in commonsense_statistic} for level, days in commonsense_statistic.items(): for day, dicts in days.items(): for dct in dicts: if dct: for key, data in dct.items(): true_count, false_count = count_true_false(data) if key not in result[level][day]: result[level][day][key] = {"true": 0, "false": 0} result[level][day][key]["true"] += true_count result[level][day][key]["false"] += false_count return result def eval_score(validation_or_test: str, file_path: str, TOKEN): if validation_or_test == 'validation': query_data_list = load_dataset('osunlp/TravelBenchEval','validation',token=TOKEN)['validation'] elif validation_or_test == 'test': query_data_list = load_dataset('osunlp/TravelBenchEval','test',token=TOKEN)['test'] query_data_list = [x for x in query_data_list] hardConstraint_statistic= {level:{day:[] for day in [3,5,7]} for level in ['easy','medium','hard']} commonsenseConstraint_statistic = {level:{day:[] for day in [3,5,7]} for level in ['easy','medium','hard']} tested_plans = load_line_json_data(file_path) delivery_cnt = 0 plan_constraint_store = [] for idx in tqdm(range(0,len(query_data_list))): query_data = query_data_list[idx] tested_plan = tested_plans[idx] if type(query_data) == str: query_data = eval(query_data) if type(tested_plan) == str: tested_plan = eval(tested_plan) if type(query_data['local_constraint']) == str: query_data['local_constraint'] = eval(query_data['local_constraint']) if tested_plan['plan']: delivery_cnt += 1 commonsense_info_box = commonsense_eval(query_data,tested_plan['plan']) else: commonsense_info_box = None if commonsense_info_box and commonsense_info_box['is_not_absent'][0] and commonsense_info_box['is_valid_information_in_sandbox'][0]: hard_info_box = hard_eval(query_data,tested_plan['plan']) else: hard_info_box = None plan_constraint_store.append({'commonsense_constraint':commonsense_info_box,'hard_constraint':hard_info_box}) commonsenseConstraint_statistic[query_data['level']][query_data['days']].append(commonsense_info_box) hardConstraint_statistic[query_data['level']][query_data['days']].append(hard_info_box) commonsenseConstraint_statistic_processed = statistics(commonsenseConstraint_statistic) hardConstraint_statistic_processed = statistics(hardConstraint_statistic) # print(commonsenseConstraint_statistic_processed) # print(hardConstraint_statistic_processed) constraint_record = {key: {day: {'house rule':0, 'cuisine':0, 'room type':0, 'transportation':0} for day in [3,5,7]} for key in ['medium','hard']} constraint_mapping = {'house rule':'valid_room_rule','cuisine':'valid_cuisine','room type':'valid_room_type','transportation':'valid_transportation'} mapping_constraint_record = {key: {day: {'valid_room_rule':0, 'valid_cuisine':0, 'valid_room_type':0, 'valid_transportation':0} for day in [3,5,7]} for key in ['medium','hard']} count_record = {key:{day:0 for day in [3,5,7]} for key in ['easy','medium','hard']} for unit in query_data_list: count_record[unit['level']][unit['days']] += 1 for key in constraint_record['medium'][3]: if unit['local_constraint'][key] != None: constraint_record[unit['level']][unit['days']][key] += 1 mapping_constraint_record[unit['level']][unit['days']][constraint_mapping[key]] += 1 data_record = {key:{day:[] for day in [3,5,7]} for key in ['easy','medium','hard']} constraint_dis_record = {"commonsense":{"pass":0,"total":0},"hard":{"pass":0,"total":0}} for constraint in ['commonsense','hard']: if constraint == 'commonsense': constraint_statistic = commonsenseConstraint_statistic_processed elif constraint == 'hard': constraint_statistic = hardConstraint_statistic_processed key_dict = {'commonsense':['is_valid_information_in_current_city','is_valid_information_in_sandbox','is_reasonalbe_visiting_city','is_valid_restaurants','is_valid_transportation','is_valid_attractions','is_valid_accommodation','is_not_absent'],'hard':['valid_cost','valid_room_rule','valid_cuisine','valid_room_type','valid_transportation']} for key in constraint_statistic: # level for key2 in constraint_statistic[key]: # day # print(key2) # key2 = eval(key2) if key2 == -1: print(constraint_statistic[key]) exit(0) for key3 in key_dict[constraint]: data_record[key][key2].append('0/0') if key3 in constraint_statistic[key][key2]: constraint_dis_record[constraint]['pass'] += constraint_statistic[key][key2][key3]['true'] if constraint == 'hard': if key == 'hard' and key3 in ['valid_room_rule','valid_cuisine','valid_room_type','valid_transportation']: data_record[key][key2][-1] = f"{constraint_statistic[key][key2][key3]['true']}/{mapping_constraint_record[key][key2][key3]}" constraint_dis_record[constraint]['total'] += mapping_constraint_record[key][key2][key3] elif key == 'medium' and key3 in ['valid_room_rule','valid_cuisine','valid_room_type']: data_record[key][key2][-1] = f"{constraint_statistic[key][key2][key3]['true']}/{mapping_constraint_record[key][key2][key3]}" constraint_dis_record[constraint]['total'] += mapping_constraint_record[key][key2][key3] else: data_record[key][key2][-1] = f"{constraint_statistic[key][key2][key3]['true']}/{count_record[key][key2]}" if key3 in ['valid_cost','valid_visitng_city_number','valid_days']: constraint_dis_record[constraint]['total'] += count_record[key][key2] else: data_record[key][key2][-1] = f"{constraint_statistic[key][key2][key3]['true']}/{count_record[key][key2]}" constraint_dis_record[constraint]['total'] += count_record[key][key2] final_all_cnt = 0 final_commonsense_cnt = 0 final_hardConstraint_cnt = 0 final_all_cnt_map = {level:0 for level in ['easy','medium','hard']} for idx in (range(0,len(query_data_list))): if plan_constraint_store[idx]['commonsense_constraint']: final_commonsense_pass = True final_hardConstraint_pass = True for item in plan_constraint_store[idx]['commonsense_constraint']: if plan_constraint_store[idx]['commonsense_constraint'][item][0] is not None and not plan_constraint_store[idx]['commonsense_constraint'][item][0]: final_commonsense_pass = False break if plan_constraint_store[idx]['hard_constraint'] is None: continue for item in plan_constraint_store[idx]['hard_constraint']: if plan_constraint_store[idx]['hard_constraint'][item][0] is not None and plan_constraint_store[idx]['hard_constraint'][item][0] == False: final_hardConstraint_pass = False break if final_commonsense_pass: final_commonsense_cnt += 1 if final_hardConstraint_pass: final_hardConstraint_cnt += 1 if final_commonsense_pass and final_hardConstraint_pass: final_all_cnt += 1 final_all_cnt_map[query_data_list[idx]['level']] += 1 result = {} if validation_or_test == 'validation': result['Delivery Rate'] = delivery_cnt / 180 result['Commonsense Constraint Micro Pass Rate'] = constraint_dis_record['commonsense']['pass'] / 1440 result['Commonsense Constraint Macro Pass Rate'] = final_commonsense_cnt / 180 result['Hard Constraint Micro Pass Rate'] = constraint_dis_record['hard']['pass'] / 420 result['Hard Constraint Macro Pass Rate'] = final_hardConstraint_cnt / 180 result['Final Pass Rate'] = final_all_cnt / 180 elif validation_or_test == 'test': result['Delivery Rate'] = delivery_cnt / 1000 result['Commonsense Constraint Micro Pass Rate'] = constraint_dis_record['commonsense']['pass'] / 8000 result['Commonsense Constraint Macro Pass Rate'] = final_commonsense_cnt / 1000 result['Hard Constraint Micro Pass Rate'] = constraint_dis_record['hard']['pass'] / 2290 result['Hard Constraint Macro Pass Rate'] = final_hardConstraint_cnt / 1000 result['Final Pass Rate'] = final_all_cnt / 1000 return result