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