jordane commited on
Commit
c68710d
1 Parent(s): cd1909c

upoad corpus

Browse files
corpus.jsonl.gz ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:fb000d01a3cf2db6be6bfdafe60f9e9c30ee5d7b219aa87bfd40b0be8dedfe8d
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+ size 1827739161
msmarco-passage-corpus-with-query.py ADDED
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+ # coding=utf-8
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+ # 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.Wikipedia
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+
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+ # Lint as: python3
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+ """MsMarco Passage dataset."""
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+
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+ import json
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+
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+ import datasets
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+
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+ _CITATION = """
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+ @misc{bajaj2018ms,
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+ title={MS MARCO: A Human Generated MAchine Reading COmprehension Dataset},
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+ author={Payal Bajaj and Daniel Campos and Nick Craswell and Li Deng and Jianfeng Gao and Xiaodong Liu
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+ and Rangan Majumder and Andrew McNamara and Bhaskar Mitra and Tri Nguyen and Mir Rosenberg and Xia Song
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+ and Alina Stoica and Saurabh Tiwary and Tong Wang},
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+ year={2018},
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+ eprint={1611.09268},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL}
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+ }
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+ """
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+
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+ _DESCRIPTION = "dataset load script for MSMARCO Passage Corpus"
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+
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+ _DATASET_URLS = {
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+ 'train': "https://huggingface.co/datasets/jordane95/msmarco-passage-corpus-with-query/resolve/main/corpus.jsonl.gz",
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+ }
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+
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+
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+ class MsMarcoPassageCorpusWithQuery(datasets.GeneratorBasedBuilder):
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+ VERSION = datasets.Version("0.0.1")
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+
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+ BUILDER_CONFIGS = [
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+ datasets.BuilderConfig(version=VERSION,
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+ description="MS MARCO Passage Corpus with Query"),
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+ ]
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+
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+ def _info(self):
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+ features = datasets.Features(
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+ {'docid': datasets.Value('string'), 'title': datasets.Value('string'), 'text': datasets.Value('string'), 'queries': [datasets.Value('string')]}
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+ )
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+
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+ return datasets.DatasetInfo(
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+ # This is the description that will appear on the datasets page.
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+ description=_DESCRIPTION,
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+ # This defines the different columns of the dataset and their types
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+ features=features, # Here we define them above because they are different between the two configurations
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+ supervised_keys=None,
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+ # Homepage of the dataset for documentation
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+ homepage="",
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+ # License for the dataset if available
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+ license="",
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+ # Citation for the dataset
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+ citation=_CITATION,
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ if self.config.data_files:
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+ downloaded_files = self.config.data_files
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+ else:
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+ downloaded_files = dl_manager.download_and_extract(_DATASET_URLS)
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+ splits = [
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+ datasets.SplitGenerator(
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+ name=split,
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+ gen_kwargs={
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+ "files": [downloaded_files[split]] if isinstance(downloaded_files[split], str) else downloaded_files[split],
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+ },
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+ ) for split in downloaded_files
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+ ]
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+ return splits
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+
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+ def _generate_examples(self, files):
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+ """Yields examples."""
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+ for filepath in files:
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+ with open(filepath, encoding="utf-8") as f:
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+ for line in f:
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+ data = json.loads(line)
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+ yield data['docid'], data