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import json |
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import csv |
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import os |
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import datasets |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = "BEIR Benchmark" |
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_DATASETS = ["fiqa", "trec-covid"] |
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URL = "" |
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_URLs = { |
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dataset: { |
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"corpus": URL + f"{dataset}/corpus.jsonl", |
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} for dataset in _DATASETS} |
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class BEIR(datasets.GeneratorBasedBuilder): |
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"""BEIR BenchmarkDataset.""" |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig( |
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name=dataset, |
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description=f"This is the {dataset} dataset in BEIR Benchmark.", |
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) for dataset in _DATASETS |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features({ |
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"_id": 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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supervised_keys=None, |
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) |
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def _split_generators(self, dl_manager): |
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"""Returns SplitGenerators.""" |
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my_urls = _URLs[self.config.name] |
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data_dir = dl_manager.download_and_extract(my_urls) |
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return [ |
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datasets.SplitGenerator( |
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name="corpus", |
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gen_kwargs={"corpus_path": data_dir["corpus"]} |
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), |
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] |
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def _generate_examples(self, corpus_path): |
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"""Yields examples.""" |
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with open(corpus_path, encoding="utf-8") as f: |
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texts = f.readlines() |
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for i, text in enumerate(texts): |
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yield i, json.loads(text) |
