sacrebleu_manual / sacrebleu_manual.py
clefourrier's picture
clefourrier HF Staff
Update sacrebleu_manual.py
e5f9604
"""
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.
We defer citations and descriptions of the many translations tasks used
here to the SacreBLEU repo from which we've obtained the datasets:
https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/dataset.py
Homepage: https://github.com/mjpost/sacrebleu/blob/master/sacrebleu/dataset.py
"""
from sacrebleu import sacrebleu
import datasets
import os
import json
_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",
}
"""
class SacrebleuManual(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
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("string"),
}
)
return datasets.DatasetInfo(
description=f"Sacrebleu\n{self.config.description}",
features=features,
homepage="",
license="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
downloaded_files = dl_manager.download(f"{os.path.join(*self.config.name.split('_'))}.jsonl")
print(downloaded_files)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"path": downloaded_files},
)
]
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
def _generate_examples(self, path):
with open(path, encoding="utf-8") as f:
for key, row in enumerate(f):
yield key, json.loads(row)