squad.py

# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import collections
import json
import os

from paddle.dataset.common import md5file
from paddle.utils.download import get_path_from_url

from ..utils.env import DATA_HOME
from .dataset import DatasetBuilder

__all__ = ["SQuAD"]


class SQuAD(DatasetBuilder):
    """
    Stanford Question Answering Dataset (SQuAD) is a reading comprehension
    dataset, consisting of questions posed by crowdworkers on a set of Wikipedia
    articles, where the answer to every question is a segment of text, or span,
    from the corresponding reading passage, or the question might be unanswerable.
    """

    META_INFO = collections.namedtuple("META_INFO", ("file", "md5", "URL"))
    SPLITS = {
        "train_v1": META_INFO(
            os.path.join("train-v1.1.json"),
            "981b29407e0affa3b1b156f72073b945",
            "https://bj.bcebos.com/paddlenlp/datasets/squad/train-v1.1.json",
        ),
        "dev_v1": META_INFO(
            os.path.join("dev-v1.1.json"),
            "3e85deb501d4e538b6bc56f786231552",
            "https://bj.bcebos.com/paddlenlp/datasets/squad/dev-v1.1.json",
        ),
        "train_v2": META_INFO(
            os.path.join("train-v2.0.json"),
            "62108c273c268d70893182d5cf8df740",
            "https://bj.bcebos.com/paddlenlp/datasets/squad/train-v2.0.json",
        ),
        "dev_v2": META_INFO(
            os.path.join("dev-v2.0.json"),
            "246adae8b7002f8679c027697b0b7cf8",
            "https://bj.bcebos.com/paddlenlp/datasets/squad/dev-v2.0.json",
        ),
    }

    def _get_data(self, mode, **kwargs):
        default_root = os.path.join(DATA_HOME, self.__class__.__name__)
        filename, data_hash, URL = self.SPLITS[mode]
        fullname = os.path.join(default_root, filename)
        if not os.path.exists(fullname) or (data_hash and not md5file(fullname) == data_hash):
            get_path_from_url(URL, default_root)

        return fullname

    def _read(self, filename, *args):
        with open(filename, "r", encoding="utf8") as f:
            input_data = json.load(f)["data"]
        for entry in input_data:
            title = entry.get("title", "").strip()
            for paragraph in entry["paragraphs"]:
                context = paragraph["context"].strip()
                for qa in paragraph["qas"]:
                    qas_id = qa["id"]
                    question = qa["question"].strip()
                    answer_starts = []
                    answers = []
                    is_impossible = False

                    if "is_impossible" in qa.keys():
                        is_impossible = qa["is_impossible"]

                    answer_starts = [answer["answer_start"] for answer in qa.get("answers", [])]
                    answers = [answer["text"].strip() for answer in qa.get("answers", [])]

                    yield {
                        "id": qas_id,
                        "title": title,
                        "context": context,
                        "question": question,
                        "answers": answers,
                        "answer_starts": answer_starts,
                        "is_impossible": is_impossible,
                    }