wehub-resource-sync
74 lines
3.0 KiB
Python
74 lines
3.0 KiB
Python
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import collections
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import json
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import os
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from paddle.dataset.common import md5file
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from paddle.utils.download import get_path_from_url
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from ..utils.env import DATA_HOME
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from .dataset import DatasetBuilder
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__all__ = ["DuReaderRobust"]
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class DuReaderRobust(DatasetBuilder):
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"""
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The machine reading comprehension dataset (i.e. DuReader robust) is designed
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to measure the robustness of a reading comprehension model, including the
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over-sensitivity, over-stability and generalization ability of the model.
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"""
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URL = "https://bj.bcebos.com/paddlenlp/datasets/dureader_robust-data.tar.gz"
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MD5 = "82f3d191a115ec17808856866787606e"
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META_INFO = collections.namedtuple("META_INFO", ("file", "md5"))
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SPLITS = {
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"train": META_INFO(os.path.join("dureader_robust-data", "train.json"), "800a3dcb742f9fdf9b11e0a83433d4be"),
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"dev": META_INFO(os.path.join("dureader_robust-data", "dev.json"), "ae73cec081eaa28a735204c4898a2222"),
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"test": META_INFO(os.path.join("dureader_robust-data", "test.json"), "e0e8aa5c7b6d11b6fc3935e29fc7746f"),
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}
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def _get_data(self, mode, **kwargs):
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default_root = os.path.join(DATA_HOME, self.__class__.__name__)
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filename, data_hash = self.SPLITS[mode]
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fullname = os.path.join(default_root, filename)
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if not os.path.exists(fullname) or (data_hash and not md5file(fullname) == data_hash):
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get_path_from_url(self.URL, default_root, self.MD5)
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return fullname
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def _read(self, filename, *args):
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with open(filename, "r", encoding="utf8") as f:
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input_data = json.load(f)["data"]
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for entry in input_data:
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title = entry.get("title", "").strip()
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for paragraph in entry["paragraphs"]:
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context = paragraph["context"].strip()
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for qa in paragraph["qas"]:
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qas_id = qa["id"]
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question = qa["question"].strip()
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answer_starts = [answer["answer_start"] for answer in qa.get("answers", [])]
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answers = [answer["text"].strip() for answer in qa.get("answers", [])]
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yield {
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"id": qas_id,
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"title": title,
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"context": context,
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"question": question,
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"answers": answers,
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"answer_starts": answer_starts,
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}
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