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"""
NOTE: This file implements translation tasks using datasets from WMT conferences,
provided by sacrebleu. Traditionally they are evaluated with BLEU scores. TER
and CHRF are other options.
Homepage: https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/dataset.py
"""
import os
import pycountry
from sacrebleu import sacrebleu
import datasets
_CITATION = """
@inproceedings{post-2018-call,
title = "A Call for Clarity in Reporting {BLEU} Scores",
author = "Post, Matt",
booktitle = "Proceedings of the Third Conference on Machine Translation: Research Papers",
month = oct,
year = "2018",
address = "Belgium, Brussels",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/W18-6319",
pages = "186--191",
}
"""
sacrebleu_datasets = sacrebleu.DATASETS
class Sacrebleu(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [
datasets.BuilderConfig(name=f"{name.replace('/', '__')}__{langpair}", version=datasets.Version("1.0.0"), description="")
for name in sacrebleu.get_available_testsets()
for langpair in sacrebleu.get_langpairs_for_testset(name)
]
def _info(self):
features = datasets.Features(
{
"translation": datasets.Value("dict"),
}
)
return datasets.DatasetInfo(
description=f"{_DESCRIPTION}\n{self.config.description}",
features=features,
homepage="",
license="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={path: f"{self.config.name}.jsonl"},
)
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, path):
with open(os.path.join(path.split("__")), encoding="utf-8") as f:
for key, row in enumerate(f):
yield key, json.loads(row)
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