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#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse
from collections import defaultdict
import json
import os
import sys
pwd = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(pwd, "../../"))
from datasets import load_dataset, DownloadMode
from tqdm import tqdm
from language_identification import LANGUAGE_MAP
from project_settings import project_path
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument("--dataset_path", default="NbAiLab/nbnn_language_detection", type=str)
parser.add_argument(
"--dataset_cache_dir",
default=(project_path / "hub_datasets").as_posix(),
type=str
)
parser.add_argument(
"--output_file",
default=(project_path / "data/nbnn.jsonl"),
type=str
)
args = parser.parse_args()
return args
def main():
args = get_args()
dataset_dict = load_dataset(
path=args.dataset_path,
cache_dir=args.dataset_cache_dir,
# download_mode=DownloadMode.FORCE_REDOWNLOAD
streaming=True
)
print(dataset_dict)
language_map = {
"nno": "no-n",
"nob": "no-b"
}
split_map = {
"dev": "validation",
"validate": "validation"
}
text_set = set()
counter = defaultdict(int)
with open(args.output_file, "w", encoding="utf-8") as f:
for k, v in dataset_dict.items():
if k in split_map.keys():
split = split_map[k]
else:
split = k
if split not in ("train", "validation", "test"):
print("skip split: {}".format(split))
continue
for sample in tqdm(v):
text = sample["text"]
language = sample["language"]
language = language_map[language]
text = text.strip()
if text in text_set:
continue
text_set.add(text)
if language not in LANGUAGE_MAP.keys():
raise AssertionError(language)
row = {
"text": text,
"language": language,
"data_source": "nbnn",
"split": split
}
row = json.dumps(row, ensure_ascii=False)
f.write("{}\n".format(row))
counter[split] += 1
print("counter: {}".format(counter))
return
if __name__ == '__main__':
main()