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wiki_lingua / wiki_lingua.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.
"""TODO: Add a description here."""
from __future__ import absolute_import, division, print_function
import pickle
import datasets
# Find for instance the citation on arxiv or on the dataset repo/website
_CITATION = """\
@article{ladhak-wiki-2020,
title = {WikiLingua: A New Benchmark Dataset for Multilingual Abstractive Summarization},
authors = {Faisal Ladhak, Esin Durmus, Claire Cardie and Kathleen McKeown},
journal = {arXiv preprint arXiv:2010.03093},
year = {2020},
url = {https://arxiv.org/abs/2010.03093}
}
"""
_DESCRIPTION = """\
WikiLingua is a large-scale multilingual dataset for the evaluation of
crosslingual abstractive summarization systems. The dataset includes ~770k
article and summary pairs in 18 languages from WikiHow. The gold-standard
article-summary alignments across languages was done by aligning the images
that are used to describe each how-to step in an article.
"""
_HOMEPAGE = "https://github.com/esdurmus/Wikilingua"
_LICENSE = "CC BY-NC-SA 3.0"
# Download links
_URLs = {
"arabic": "https://drive.google.com/uc?export=download&id=1__EjA6oZsgXQpggPm-h54jZu3kP6Y6zu",
"chinese": "https://drive.google.com/uc?export=download&id=1TuWH7uwu6V90QWmZn25qhou1rm97Egmn",
"czech": "https://drive.google.com/uc?export=download&id=1GcUN6mytEcOMBBOvjJOQzBmEkc-LdgQg",
"dutch": "https://drive.google.com/uc?export=download&id=1-w-0uqaC6hnRn1F_3XqJEvi09zlcTIhX",
"english": "https://drive.google.com/uc?export=download&id=11wMGqNVSwwk6zUnDaJEgm3qT71kAHeff",
"french": "https://drive.google.com/uc?export=download&id=1Uit4Og1pk-br_0UJIO5sdhApyhTuHzqo",
"german": "https://drive.google.com/uc?export=download&id=1meSNZHxd_0TZLKCRCYGN-Ke3IA5c1qOE",
"hindi": "https://drive.google.com/uc?export=download&id=1ZyFGufe4puX3vjGPbp4xg9Hca3Gwq22g",
"indonesian": "https://drive.google.com/uc?export=download&id=1PGa8j1_IqxiGTc3SU6NMB38sAzxCPS34",
"italian": "https://drive.google.com/uc?export=download&id=1okwGJiOZmTpNRNgJLCnjFF4Q0H1z4l6_",
"japanese": "https://drive.google.com/uc?export=download&id=1Z2ty5hU0tIGRZRDlFQZLO7b5vijRfvo0",
"korean": "https://drive.google.com/uc?export=download&id=1cqu_YAgvlyVSzzjcUyP1Cz7q0k8Pw7vN",
"portuguese": "https://drive.google.com/uc?export=download&id=1GTHUJxxmjLmG2lnF9dwRgIDRFZaOY3-F",
"russian": "https://drive.google.com/uc?export=download&id=1fUR3MqJ8jTMka6owA0S-Fe6aHmiophc_",
"spanish": "https://drive.google.com/uc?export=download&id=17FGi8KI9N9SuGe7elM8qU8_3fx4sfgTr",
"thai": "https://drive.google.com/uc?export=download&id=1QsV8C5EPJrQl37mwva_5-IJOrCaOi2tH",
"turkish": "https://drive.google.com/uc?export=download&id=1M1M5yIOyjKWGprc3LUeVVwxgKXxgpqxm",
"vietnamese": "https://drive.google.com/uc?export=download&id=17FGi8KI9N9SuGe7elM8qU8_3fx4sfgTr",
}
class WikiLingua(datasets.GeneratorBasedBuilder):
"""TODO: Short description of my dataset."""
VERSION = datasets.Version("1.1.0")
# This is an example of a dataset with multiple configurations.
# If you don't want/need to define several sub-sets in your dataset,
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes.
# If you need to make complex sub-parts in the datasets with configurable options
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig
# BUILDER_CONFIG_CLASS = MyBuilderConfig
# You will be able to load one or the other configurations in the following list with
# data = datasets.load_dataset('my_dataset', 'first_domain')
# data = datasets.load_dataset('my_dataset', 'second_domain')
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="arabic", version=VERSION, description="A subset of article-summary in Arabic"),
datasets.BuilderConfig(name="chinese", version=VERSION, description="A subset of article-summary in Chinese"),
datasets.BuilderConfig(name="czech", version=VERSION, description="A subset of article-summary in Czech"),
datasets.BuilderConfig(name="dutch", version=VERSION, description="A subset of article-summary in Dutch"),
datasets.BuilderConfig(name="english", version=VERSION, description="A subset of article-summary in English"),
datasets.BuilderConfig(name="french", version=VERSION, description="A subset of article-summary in French"),
datasets.BuilderConfig(name="german", version=VERSION, description="A subset of article-summary in German"),
datasets.BuilderConfig(name="hindi", version=VERSION, description="A subset of article-summary in Hindi"),
datasets.BuilderConfig(
name="indonesian", version=VERSION, description="A subset of article-summary in Indonesian"
),
datasets.BuilderConfig(name="italian", version=VERSION, description="A subset of article-summary in Italian"),
datasets.BuilderConfig(
name="japanese", version=VERSION, description="A subset of article-summary in Japanese"
),
datasets.BuilderConfig(name="korean", version=VERSION, description="A subset of article-summary in Korean"),
datasets.BuilderConfig(
name="portuguese", version=VERSION, description="A subset of article-summary in Portuguese"
),
datasets.BuilderConfig(name="russian", version=VERSION, description="A subset of article-summary in Russian"),
datasets.BuilderConfig(name="spanish", version=VERSION, description="A subset of article-summary in Spanish"),
datasets.BuilderConfig(name="thai", version=VERSION, description="A subset of article-summary in Thai"),
datasets.BuilderConfig(name="turkish", version=VERSION, description="A subset of article-summary in Turkish"),
datasets.BuilderConfig(
name="vietnamese", version=VERSION, description="A subset of article-summary in Vietnamese"
),
]
DEFAULT_CONFIG_NAME = "english"
def _info(self):
if self.config.name == "english":
features = datasets.Features(
{
"url": datasets.Value("string"),
"article": datasets.Sequence(
{
"section_name": datasets.Value("string"),
"document": datasets.Value("string"),
"summary": datasets.Value("string"),
}
),
}
)
else:
features = datasets.Features(
{
"url": datasets.Value("string"),
"article": datasets.Sequence(
{
"section_name": datasets.Value("string"),
"document": datasets.Value("string"),
"summary": datasets.Value("string"),
"english_url": datasets.Value("string"),
"english_section_name": datasets.Value("string"),
}
),
}
)
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# This defines the different columns of the dataset and their types
features=features, # Here we define them above because they are different between the two configurations
# If there's a common (input, target) tuple from the features,
# specify them here. They'll be used if as_supervised=True in
# builder.as_dataset.
supervised_keys=None,
# Homepage of the dataset for documentation
homepage=_HOMEPAGE,
# License for the dataset if available
license=_LICENSE,
# Citation for the dataset
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
my_urls = _URLs[self.config.name]
# See create_dummy.py to create new dummy data
train_fname = dl_manager.download_and_extract(my_urls)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={
"filepath": train_fname,
"split": "train",
},
),
]
def _process_article(self, article):
"""Parse the article and convert into list of dict"""
processed_article = []
for key, value in article.items():
row = {"section_name": key, "document": value["document"], "summary": value["summary"]}
if self.config.name != "english":
row["english_url"] = value["english_url"]
row["english_section_name"] = value["english_section_name"]
processed_article.append(row)
return processed_article
def _generate_examples(self, filepath, split):
""" Yields examples. """
with open(filepath, "rb") as f:
data = pickle.load(f)
for id_, row in enumerate(data.items()):
yield id_, {"url": row[0], "article": self._process_article(row[1])}