Datasets:

Samsung
/

samsum

	# 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.
	"""SAMSum dataset."""


	import json

	import py7zr

	import datasets


	_CITATION = """
	@article{gliwa2019samsum,
	title={SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization},
	author={Gliwa, Bogdan and Mochol, Iwona and Biesek, Maciej and Wawer, Aleksander},
	journal={arXiv preprint arXiv:1911.12237},
	year={2019}
	}
	"""

	_DESCRIPTION = """
	SAMSum Corpus contains over 16k chat dialogues with manually annotated
	summaries.
	There are two features:
	- dialogue: text of dialogue.
	- summary: human written summary of the dialogue.
	- id: id of a example.
	"""

	_HOMEPAGE = "https://arxiv.org/abs/1911.12237"

	_LICENSE = "CC BY-NC-ND 4.0"

	_URL = "https://huggingface.co/datasets/samsum/resolve/main/data/corpus.7z"


	class Samsum(datasets.GeneratorBasedBuilder):
	"""SAMSum Corpus dataset."""

	VERSION = datasets.Version("1.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="samsum"),
	]

	def _info(self):
	features = datasets.Features(
	{
	"id": datasets.Value("string"),
	"dialogue": datasets.Value("string"),
	"summary": datasets.Value("string"),
	}
	)
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	path = dl_manager.download(_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": (path, "train.json"),
	"split": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": (path, "test.json"),
	"split": "test",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": (path, "val.json"),
	"split": "val",
	},
	),
	]

	def _generate_examples(self, filepath, split):
	"""Yields examples."""
	path, fname = filepath
	with open(path, "rb") as f:
	with py7zr.SevenZipFile(f, "r") as z:
	for name, bio in z.readall().items():
	if name == fname:
	data = json.load(bio)
	for example in data:
	yield example["id"], example