| import os.path as osp |
| import json |
| import pandas as pd |
|
|
|
|
|
|
| def get_qsn_type(qsn, ans_rsn): |
| dos = ['does', 'do', 'did'] |
| bes = ['was', 'were', 'is', 'are'] |
| w5h1 = ['what', 'who', 'which', 'why', 'how', 'where'] |
| qsn_sp = qsn.split() |
| type = qsn_sp[0].lower() |
| if type == 'what': |
| if qsn_sp[1].lower() in dos: |
| type = 'whata' |
| elif qsn_sp[1].lower() in bes: |
| type = 'whatb' |
| else: |
| type = 'whato' |
| elif type == 'how': |
| if qsn_sp[1].lower() == 'many': |
| type = 'howm' |
| elif type not in w5h1: |
| type = 'other' |
| if ans_rsn in ['pr', 'cr']: |
| |
| type += 'r' |
| return type |
|
|
|
|
| def group(csv_data, gt=True): |
| ans_group, qsn_group = {}, {} |
| for idx, row in csv_data.iterrows(): |
| qsn, ans = row['question'], row['answer'] |
| if gt: |
| type = row['type'] |
| if type == 'TP': type = 'TN' |
| else: |
| type = 'null' if 'type' not in row else row['type'] |
| type = get_qsn_type(qsn, type) |
| if type not in ans_group: |
| ans_group[type] = {ans} |
| qsn_group[type] = {qsn} |
| else: |
| ans_group[type].add(ans) |
| qsn_group[type].add(qsn) |
| return ans_group, qsn_group |
|
|
|
|
| def load_model_by_key(cur_model, model_path): |
| model_dict = torch.load(model_path) |
| new_model_dict = {} |
| for k, v in cur_model.state_dict().items(): |
| if k in model_dict: |
| v = model_dict[k] |
| else: |
| pass |
| |
| new_model_dict[k] = v |
| return new_model_dict |
|
|
|
|
| def load_file(filename): |
| file_type = osp.splitext(filename)[-1] |
| if file_type == '.csv': |
| data = pd.read_csv(filename) |
| else: |
| with open(filename, 'r') as fp: |
| if file_type == '.json': |
| data = json.load(fp) |
| elif file_type == '.txt': |
| data = fp.readlines() |
| data = [datum.rstrip('\n') for datum in data] |
| return data |
|
|
