Datasets:
kor_sarcasm

	# 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.
	"""Korean Sarcasm Detection Dataset"""


	import csv

	import datasets
	from datasets.tasks import TextClassification


	_DESCRIPTION = """\
	This is a dataset designed to detect sarcasm in Korean because it distorts the literal meaning of a sentence
	and is highly related to sentiment classification.
	"""

	_HOMEPAGE = "https://github.com/SpellOnYou/korean-sarcasm"

	_LICENSE = "MIT License"

	_TRAIN_DOWNLOAD_URL = "https://raw.githubusercontent.com/SpellOnYou/korean-sarcasm/master/data/jiwon/train.csv"
	_TEST_DOWNLOAD_URL = "https://raw.githubusercontent.com/SpellOnYou/korean-sarcasm/master/data/jiwon/test.csv"


	class KorSarcasm(datasets.GeneratorBasedBuilder):
	"""Korean Sarcasm Detection Dataset"""

	VERSION = datasets.Version("1.1.0")

	def _info(self):

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"tokens": datasets.Value("string"),
	"label": datasets.features.ClassLabel(names=["no_sarcasm", "sarcasm"]),
	}
	),
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	task_templates=[TextClassification(text_column="tokens", label_column="label")],
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""

	train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
	test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
	return [
	datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
	datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
	]

	def _generate_examples(self, filepath):
	"""Generate Korean sarcasm examples"""

	with open(filepath, encoding="utf-8") as csv_file:
	data = csv.reader(csv_file, delimiter=",")
	next(data, None)
	for id_, row in enumerate(data):
	row = row[1:3]
	tokens, label = row
	yield id_, {"tokens": tokens, "label": int(label)}