Delete beir-corpus.py
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beir-corpus.py
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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.
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# Lint as: python3
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import json
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import datasets
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_CITATION = '''
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@inproceedings{
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thakur2021beir,
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title={{BEIR}: A Heterogeneous Benchmark for Zero-shot Evaluation of Information Retrieval Models},
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author={Nandan Thakur and Nils Reimers and Andreas R{\"u}ckl{\'e} and Abhishek Srivastava and Iryna Gurevych},
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booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2)},
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year={2021},
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url={https://openreview.net/forum?id=wCu6T5xFjeJ}
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}
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'''
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all_data = [
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'arguana',
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'climate-fever',
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'cqadupstack-android',
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'cqadupstack-english',
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'cqadupstack-gaming',
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'cqadupstack-gis',
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'cqadupstack-mathematica',
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'cqadupstack-physics',
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'cqadupstack-programmers',
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'cqadupstack-stats',
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'cqadupstack-tex',
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'cqadupstack-unix',
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'cqadupstack-webmasters',
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'cqadupstack-wordpress',
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'dbpedia-entity',
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'fever',
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'fiqa',
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'hotpotqa',
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'nfcorpus',
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'quora',
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'scidocs',
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'scifact',
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'trec-covid',
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'webis-touche2020',
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'nq'
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]
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_DESCRIPTION = 'dataset load script for BEIR corpus'
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_DATASET_URLS = {
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data: {
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'train': f'https://huggingface.co/datasets/Tevatron/beir-corpus/resolve/main/{data}.jsonl.gz',
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} for data in all_data
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}
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class BeirCorpus(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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version=datasets.Version('1.1.0'),
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name=data,
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description=f'BEIR dataset corpus {data}.'
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) for data in all_data
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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'),
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'title': datasets.Value('string'),
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'text': datasets.Value('string'),
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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='https://github.com/beir-cellar/beir',
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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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def _split_generators(self, dl_manager):
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data = self.config.name
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downloaded_files = dl_manager.download_and_extract(_DATASET_URLS[data])
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splits = [
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datasets.SplitGenerator(
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name='train',
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gen_kwargs={
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'filepath': downloaded_files['train'],
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},
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),
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]
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return splits
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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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for line in f:
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data = json.loads(line)
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yield data['docid'], data
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