Datasets:

IlyaGusev
/

gazeta

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and Ilya Gusev
	#
	# 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.
	"""Dataset for automatic summarization of Russian news"""


	import json
	import os

	import datasets


	_CITATION = """
	@InProceedings{10.1007/978-3-030-59082-6_9,
	author="Gusev, Ilya",
	editor="Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia",
	title="Dataset for Automatic Summarization of Russian News",
	booktitle="Artificial Intelligence and Natural Language",
	year="2020",
	publisher="Springer International Publishing",
	address="Cham",
	pages="122--134",
	isbn="978-3-030-59082-6"
	}
	"""

	_DESCRIPTION = "Dataset for automatic summarization of Russian news"

	_HOMEPAGE = "https://github.com/IlyaGusev/gazeta"

	_URLs = {
	"default": "https://github.com/IlyaGusev/gazeta/releases/download/1.0/gazeta_jsonl.tar.gz",
	}

	_DOCUMENT = "text"
	_SUMMARY = "summary"


	class GazetaDataset(datasets.GeneratorBasedBuilder):
	"""Gazeta Dataset"""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="default", version=VERSION, description=""),
	]

	DEFAULT_CONFIG_NAME = "default"

	def _info(self):
	features = datasets.Features(
	{
	_DOCUMENT: datasets.Value("string"),
	_SUMMARY: datasets.Value("string"),
	"title": datasets.Value("string"),
	"date": datasets.Value("string"),
	"url": datasets.Value("string")
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=(_DOCUMENT, _SUMMARY),
	homepage=_HOMEPAGE,
	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)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "gazeta_train.jsonl"),
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "gazeta_test.jsonl"),
	"split": "test"
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": os.path.join(data_dir, "gazeta_val.jsonl"),
	"split": "dev",
	},
	),
	]

	def _generate_examples(
	self, filepath, split
	):
	with open(filepath, encoding="utf-8") as f:
	for id_, row in enumerate(f):
	data = json.loads(row)
	yield id_, data