| import re | |
| from utils import read_json_file, read_jsonl_file, write_json_file, write_jsonl_file, read_txt_file, read_csv_file, parse | |
| def reformat(args, file): | |
| path = args.input_dir + "/" + file + ".csv" | |
| data = read_csv_file(path) | |
| turns = [] | |
| for i in range(1, len(data)): | |
| ds = data[i] | |
| t = { | |
| "turn": "single", | |
| "locale": "en", | |
| "dialog": [] | |
| } | |
| d = {"role": ds[1].strip("\[\]\'"), | |
| "utterance": ds[0], | |
| "belief_state": [{"domain": None, | |
| "goal": [{"intent": None, | |
| "slot_value_table": [{"slot": 'Emotion', "value": ds[2]}, | |
| {"slot": 'Sentiment', "value": ds[4]} | |
| ]} | |
| ]} | |
| ], | |
| "querying_result": [], | |
| "summary": None, | |
| "locale": None, | |
| "topic" : None, | |
| "opinions": None, | |
| "answer": None} | |
| t["dialog"].append(d) | |
| t["knowledge"] = None | |
| turns.append(t) | |
| write_jsonl_file(turns, args.output_dir + "/" + file + ".jsonl") | |
| def preprocess(args): | |
| reformat(args, "emorynlp_train_final") | |
| reformat(args, "emorynlp_dev_final") | |
| reformat(args, "emorynlp_test_final") | |
| if __name__ == "__main__": | |
| args = parse() | |
| preprocess(args) | |