90 lines
3.0 KiB
Python
90 lines
3.0 KiB
Python
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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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 datasets
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import json
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import os
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import pandas as pd
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_CITATION = """\
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@article{2017arXivtriviaqa,
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author = {{Joshi}, Mandar and {Choi}, Eunsol and {Weld},
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Daniel and {Zettlemoyer}, Luke},
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title = "{triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension}",
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journal = {arXiv e-prints},
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year = 2017,
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eid = {arXiv:1705.03551},
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pages = {arXiv:1705.03551},
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archivePrefix = {arXiv},
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eprint = {1705.03551},
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}
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"""
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_DESCRIPTION = """\
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TriviaqQA is a reading comprehension dataset containing over 650K question-answer-evidence triples.
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"""
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_HOMEPAGE = 'https://modelscope.cn/datasets/modelscope/trivia_qa/summary'
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_URL = 'https://modelscope.cn/api/v1/datasets/modelscope/trivia_qa/repo?Revision=master&FilePath=trivia_qa.zip'
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task_list = ['default']
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class TriviaQAConfig(datasets.BuilderConfig):
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def __init__(self, **kwargs):
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super().__init__(version=datasets.Version('1.0.0'), **kwargs)
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class TriviaQA(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [TriviaQAConfig(name=task_name, ) for task_name in task_list]
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def _info(self):
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features = datasets.Features({
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'input': [{
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'role': datasets.features.Value('string'),
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'content': datasets.features.Value('string'),
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}],
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'ideal': [datasets.Value('string')],
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})
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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data_dir = dl_manager.download_and_extract(_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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'filepath': os.path.join(data_dir, 'trivia_qa/test.jsonl'),
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split('dev'),
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gen_kwargs={
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'filepath': os.path.join(data_dir, 'trivia_qa/dev.jsonl'),
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},
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),
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]
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def _generate_examples(self, filepath):
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with open(filepath, encoding='utf-8') as f:
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contents = [json.loads(line) for line in f.readlines()]
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for i, instance in enumerate(contents):
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yield i, instance
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