Datasets:
cs_restaurants

	# 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.
	"""Czech restaurant information dataset for NLG"""


	import json

	import datasets


	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\
	@article{DBLP:journals/corr/abs-1910-05298,
	author = {Ondrej Dusek and
	Filip Jurcicek},
	title = {Neural Generation for Czech: Data and Baselines},
	journal = {CoRR},
	volume = {abs/1910.05298},
	year = {2019},
	url = {http://arxiv.org/abs/1910.05298},
	archivePrefix = {arXiv},
	eprint = {1910.05298},
	timestamp = {Wed, 16 Oct 2019 16:25:53 +0200},
	biburl = {https://dblp.org/rec/journals/corr/abs-1910-05298.bib},
	bibsource = {dblp computer science bibliography, https://dblp.org}
	}
	"""

	_DESCRIPTION = """\
	This is a dataset for NLG in task-oriented spoken dialogue systems with Czech as the target language. It originated as
	a translation of the English San Francisco Restaurants dataset by Wen et al. (2015).
	"""

	_LICENSE = "Creative Commons 4.0 BY-SA"

	_URLs = {
	"CSRestaurants": "https://raw.githubusercontent.com/UFAL-DSG/cs_restaurant_dataset/master/",
	}


	class CSRestaurants(datasets.GeneratorBasedBuilder):
	"""Czech restaurant information dataset for NLG"""

	VERSION = datasets.Version("1.0.0")
	BUILDER_CONFIGS = [datasets.BuilderConfig(name="CSRestaurants", description="NLG data for Czech")]
	DEFAULT_CONFIG_NAME = "CSRestaurants"

	def _info(self):
	features = datasets.Features(
	{
	"da": datasets.Value("string"),
	"delex_da": datasets.Value("string"),
	"text": datasets.Value("string"),
	"delex_text": datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage="https://github.com/UFAL-DSG/cs_restaurant_dataset",
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	master_url = _URLs[self.config.name]
	train_path = dl_manager.download_and_extract(master_url + "train.json")
	valid_path = dl_manager.download_and_extract(master_url + "devel.json")
	test_path = dl_manager.download_and_extract(master_url + "test.json")

	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
	datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": valid_path}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
	]

	def _generate_examples(self, filepath):
	"""Yields examples."""

	with open(filepath, encoding="utf8") as f:
	data = json.load(f)
	for id_, instance in enumerate(data):
	yield id_, {
	"da": instance["da"],
	"delex_da": instance["delex_da"],
	"text": instance["text"],
	"delex_text": instance["delex_text"],
	}