vlsp / vlsp.py
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Create vlsp.py
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# coding=utf-8
# 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.
"""VLSP: Very Long Scientific Papers"""
import os
import glob
import datasets
_CITATION = """"""
_DESCRIPTION = """\
Very Long version of the scientific papers summarization dataset. Only includes theses over 10,000 tokens long.
"""
_HOMEPAGE = "https://github.com/ghomasHudson/very_long_scientific_papers"
_URL = "https://github.com/ghomasHudson/very_long_scientific_papers/archive/master.zip"
class VLSP(datasets.GeneratorBasedBuilder):
"""VLSP: Very Long Scientific Papers"""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="arxiv", description="Arxiv theses"),
]
DEFAULT_CONFIG_NAME = "arxiv"
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"abstract": datasets.features.Sequence(
datasets.Value("string")
),
"article": datasets.Value("string"),
}
),
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"filepath": os.path.join(data_dir,"very_long_scientific_papers-master", "deduped-test"),
}
)
]
def _generate_examples(self, filepath):
for key, fn in enumerate(glob.glob(os.path.join(filepath, "*.main.txt"))):
summary = []
summ_fn = fn.replace(".main.", ".abstract.")
if os.path.exists(summ_fn):
summary.append(open(summ_fn).read())
summ_fn = fn.replace(".main.", ".abstract-long.")
if os.path.exists(summ_fn):
summary.append(open(summ_fn).read())
yield key, {
"article": open(fn).read(),
"abstract": summary
}