-
Notifications
You must be signed in to change notification settings - Fork 75
/
extend_dataset.py
52 lines (37 loc) · 1.53 KB
/
extend_dataset.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
from joblib import Parallel, delayed
from textblob import TextBlob
from textblob.translate import NotTranslated
import argparse
import os
import pandas as pd
NAN_WORD = "_NAN_"
def translate(comment, language):
if hasattr(comment, "decode"):
comment = comment.decode("utf-8")
text = TextBlob(comment)
try:
text = text.translate(to=language)
text = text.translate(to="en")
except NotTranslated:
pass
return str(text)
def main():
parser = argparse.ArgumentParser("Script for extending train dataset")
parser.add_argument("train_file_path")
parser.add_argument("--languages", nargs="+", default=["es", "de", "fr"])
parser.add_argument("--thread-count", type=int, default=300)
parser.add_argument("--result-path", default="extended_data")
args = parser.parse_args()
train_data = pd.read_csv(args.train_file_path)
comments_list = train_data["comment_text"].fillna(NAN_WORD).values
if not os.path.exists(args.result_path):
os.mkdir(args.result_path)
parallel = Parallel(args.thread_count, backend="threading", verbose=5)
for language in args.languages:
print('Translate comments using "{0}" language'.format(language))
translated_data = parallel(delayed(translate)(comment, language) for comment in comments_list)
train_data["comment_text"] = translated_data
result_path = os.path.join(args.result_path, "train_" + language + ".csv")
train_data.to_csv(result_path, index=False)
if __name__ == "__main__":
main()