examples/preprocess/process_diac2019.py

#!/usr/bin/python3
# -*- coding: utf-8 -*-
import argparse
import json
import os
from pathlib import Path
import sys

pwd = os.path.abspath(os.path.dirname(__file__))
sys.path.append(os.path.join(pwd, '../../'))

from datasets import load_dataset
from lxml import etree
import pandas as pd
from tqdm import tqdm

from project_settings import project_path


def get_args():
    parser = argparse.ArgumentParser()

    parser.add_argument("--data_dir", default="./data/diac2019", type=str)
    parser.add_argument(
        "--output_file",
        default=(project_path / "data/diac2019.jsonl"),
        type=str
    )

    args = parser.parse_args()
    return args


def main():
    args = get_args()

    data_dir = Path(args.data_dir)

    with open(args.output_file, "w", encoding="utf-8") as f:
        # train_set.xml
        filename = data_dir / "train_set.xml"
        tree = etree.parse(filename.as_posix())
        root = tree.getroot()

        for group in root:
            equal = group[0]
            not_equal = group[1]

            equal_questions = [question.text for question in equal]
            not_equal_questions = [question.text for question in not_equal]

            pairs = set()

            for q1 in equal_questions:
                for q2 in equal_questions:
                    if q1 == q2:
                        continue
                    pair = (q1, q2, 1)
                    pairs.add(pair)

            for q1 in equal_questions:
                for q2 in not_equal_questions:
                    if q1 == q2:
                        continue
                    pair = (q1, q2, 0)
                    pairs.add(pair)

            for pair in pairs:
                q1, q2, label = pair

                label = str(label)
                if label not in ("0", "1", None):
                    raise AssertionError

                json_row = {
                    "sentence1": q1,
                    "sentence2": q2,
                    "label": label,
                    "data_source": "diac2019",
                    "split": "train"
                }

                json_row = json.dumps(json_row, ensure_ascii=False)
                f.write("{}\n".format(json_row))

        # dev_set.csv
        filename = data_dir / "dev_set.csv"
        df = pd.read_csv(filename.as_posix(), delimiter="\t")
        for i, row in df.iterrows():

            question1 = row["question1"]
            question2 = row["question2"]

            json_row = {
                "sentence1": question1,
                "sentence2": question2,
                "score": "1",
                "data_source": "diac2019",
                "split": "validation"
            }

            json_row = json.dumps(json_row, ensure_ascii=False)
            f.write("{}\n".format(json_row))

        # test_set.csv
        filename = data_dir / "test_set.csv"
        df = pd.read_csv(filename.as_posix(), delimiter="\t")
        for i, row in df.iterrows():

            question1 = row["question1"]
            question2 = row["question2"]

            json_row = {
                "sentence1": question1,
                "sentence2": question2,
                "score": None,
                "data_source": "diac2019",
                "split": "test"
            }

            json_row = json.dumps(json_row, ensure_ascii=False)
            f.write("{}\n".format(json_row))

    return


if __name__ == '__main__':
    main()