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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
""" STS Benchmark """
import os
import datasets
_DESCRIPTION = """STS Benchmark comprises a selection of the English datasets used in the STS tasks organized in the context of SemEval between 2012 and 2017. The selection of datasets include text from image captions, news headlines and user forums."""
_HOMEPAGE = "http://ixa2.si.ehu.eus/stswiki/index.php/STSbenchmark"
_URL = "http://ixa2.si.ehu.es/stswiki/images/4/48/Stsbenchmark.tar.gz"
class STSBenchmark(datasets.GeneratorBasedBuilder):
""" STS Benchmark """
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="all", version=VERSION),
datasets.BuilderConfig(name="news", version=VERSION),
datasets.BuilderConfig(name="captions", version=VERSION),
datasets.BuilderConfig(name="forums", version=VERSION),
]
DEFAULT_CONFIG_NAME = "all"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features({
"id": datasets.Value("int32"),
"sentence1": datasets.Value("string"),
"sentence2": datasets.Value("string"),
"score": datasets.Value("float")
}),
homepage=_HOMEPAGE,
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=str(datasets.Split.TRAIN),
gen_kwargs={
"filepath": os.path.join(data_dir, "stsbenchmark/sts-train.csv"),
},
),
datasets.SplitGenerator(
name=str(datasets.Split.VALIDATION),
gen_kwargs={
"filepath": os.path.join(data_dir, "stsbenchmark/sts-dev.csv"),
},
),
datasets.SplitGenerator(
name=str(datasets.Split.TEST),
gen_kwargs={
"filepath": os.path.join(data_dir, "stsbenchmark/sts-test.csv"),
},
),
]
def _generate_examples(self, filepath: str):
with open(filepath, encoding="utf-8") as f:
for i, row in enumerate(f):
genre, filename, year, id_, score, sent1, sent2, *_ = row.rstrip().split("\t")
genre = genre.split("-")[-1]
if self.config.name == "all" or genre == self.config.name:
yield i, {
"id": i,
"sentence1": sent1,
"sentence2": sent2,
"score": float(score),
}
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