Datasets:
wiki_asp

	# 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.
	"""Wiki Asp datasert for Multi-domain Aspect-based Summarization"""


	import json
	import os

	import datasets


	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@article{hayashi20tacl,
	title = {WikiAsp: A Dataset for Multi-domain Aspect-based Summarization},
	authors = {Hiroaki Hayashi and Prashant Budania and Peng Wang and Chris Ackerson and Raj Neervannan and Graham Neubig},
	journal = {Transactions of the Association for Computational Linguistics (TACL)},
	year = {2020},
	url = {https://arxiv.org/abs/2011.07832}
	}
	"""

	_DESCRIPTION = """\
	WikiAsp is a multi-domain, aspect-based summarization dataset in the encyclopedic
	domain. In this task, models are asked to summarize cited reference documents of a
	Wikipedia article into aspect-based summaries. Each of the 20 domains include 10
	domain-specific pre-defined aspects.
	"""

	_HOMEPAGE = "https://github.com/neulab/wikiasp"

	_LICENSE = "CC BY-SA 4.0"

	# Download links
	_URLs = {
	"album": "http://phontron.com/download/wikiasp/Album.tar.bz2",
	"animal": "http://phontron.com/download/wikiasp/Animal.tar.bz2",
	"artist": "http://phontron.com/download/wikiasp/Artist.tar.bz2",
	"building": "http://phontron.com/download/wikiasp/Building.tar.bz2",
	"company": "http://phontron.com/download/wikiasp/Company.tar.bz2",
	"educational_institution": "http://phontron.com/download/wikiasp/EducationalInstitution.tar.bz2",
	"event": "http://phontron.com/download/wikiasp/Event.tar.bz2",
	"film": "http://phontron.com/download/wikiasp/Film.tar.bz2",
	"group": "http://phontron.com/download/wikiasp/Group.tar.bz2",
	"historic_place": "http://phontron.com/download/wikiasp/HistoricPlace.tar.bz2",
	"infrastructure": "http://phontron.com/download/wikiasp/Infrastructure.tar.bz2",
	"mean_of_transportation": "http://phontron.com/download/wikiasp/MeanOfTransportation.tar.bz2",
	"office_holder": "http://phontron.com/download/wikiasp/OfficeHolder.tar.bz2",
	"plant": "http://phontron.com/download/wikiasp/Plant.tar.bz2",
	"single": "http://phontron.com/download/wikiasp/Single.tar.bz2",
	"soccer_player": "http://phontron.com/download/wikiasp/SoccerPlayer.tar.bz2",
	"software": "http://phontron.com/download/wikiasp/Software.tar.bz2",
	"television_show": "http://phontron.com/download/wikiasp/TelevisionShow.tar.bz2",
	"town": "http://phontron.com/download/wikiasp/Town.tar.bz2",
	"written_work": "http://phontron.com/download/wikiasp/WrittenWork.tar.bz2",
	}


	class WikiAsp(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="album", version=VERSION, description="A subset of dataset from the musical album domain"
	),
	datasets.BuilderConfig(
	name="animal", version=VERSION, description="A subset of dataset from the animal domain"
	),
	datasets.BuilderConfig(
	name="artist", version=VERSION, description="A subset of dataset from the artist domain"
	),
	datasets.BuilderConfig(
	name="building", version=VERSION, description="A subset of dataset from the buildings domain"
	),
	datasets.BuilderConfig(
	name="company", version=VERSION, description="A subset of dataset from the company domain"
	),
	datasets.BuilderConfig(
	name="educational_institution",
	version=VERSION,
	description="A subset of dataset from the educational institution domain",
	),
	datasets.BuilderConfig(
	name="event", version=VERSION, description="A subset of dataset from the events domain"
	),
	datasets.BuilderConfig(name="film", version=VERSION, description="A subset of dataset from the film domain"),
	datasets.BuilderConfig(name="group", version=VERSION, description="A subset of dataset from the group domain"),
	datasets.BuilderConfig(
	name="historic_place", version=VERSION, description="A subset of dataset from the historic places domain"
	),
	datasets.BuilderConfig(
	name="infrastructure", version=VERSION, description="A subset of dataset from the infrastructure domain"
	),
	datasets.BuilderConfig(
	name="mean_of_transportation",
	version=VERSION,
	description="A subset of dataset from the transportation mean domain",
	),
	datasets.BuilderConfig(
	name="office_holder", version=VERSION, description="A subset of dataset from the office holder domain"
	),
	datasets.BuilderConfig(name="plant", version=VERSION, description="A subset of dataset from the plant domain"),
	datasets.BuilderConfig(
	name="single", version=VERSION, description="A subset of dataset from the musical single domain"
	),
	datasets.BuilderConfig(
	name="soccer_player", version=VERSION, description="A subset of dataset from the soccer player domain"
	),
	datasets.BuilderConfig(
	name="software", version=VERSION, description="A subset of dataset from the software domain"
	),
	datasets.BuilderConfig(
	name="television_show", version=VERSION, description="A subset of dataset from the television show domain"
	),
	datasets.BuilderConfig(name="town", version=VERSION, description="A subset of dataset from the town domain"),
	datasets.BuilderConfig(
	name="written_work", version=VERSION, description="A subset of dataset from the written work domain"
	),
	]

	def _info(self):
	features = datasets.Features(
	{
	"exid": datasets.Value("string"),
	"inputs": datasets.Sequence(datasets.Value("string")),
	"targets": datasets.Sequence(datasets.Sequence(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]
	data_dir = dl_manager.download_and_extract(my_urls)
	data_dir = os.path.join(data_dir, self.config.name.title().replace("_", ""))
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": os.path.join(data_dir, "train.jsonl"),
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": os.path.join(data_dir, "test.jsonl"), "split": "test"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "valid.jsonl"),
	"split": "dev",
	},
	),
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""
	with open(filepath, encoding="utf-8") as f:
	for id_, row in enumerate(f):
	data = json.loads(row)
	yield id_, {
	"exid": data["exid"],
	"inputs": data["inputs"],
	"targets": data["targets"],
	}