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# 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.
"""Kinyarwanda and Kirundi news classification datasets."""
import csv
import os
import datasets
_CITATION = """\
@article{niyongabo2020kinnews,
title={KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi},
author={Niyongabo, Rubungo Andre and Qu, Hong and Kreutzer, Julia and Huang, Li},
journal={arXiv preprint arXiv:2010.12174},
year={2020}
}
"""
_DESCRIPTION = """\
Kinyarwanda and Kirundi news classification datasets
"""
_HOMEPAGE = "https://github.com/Andrews2017/KINNEWS-and-KIRNEWS-Corpus"
_LICENSE = "MIT License"
_URLs = {
"kinnews": "https://github.com/saradhix/kinnews_kirnews/raw/master/KINNEWS.zip",
"kirnews": "https://github.com/saradhix/kinnews_kirnews/raw/master/KIRNEWS.zip",
}
class KinnewsKirnews(datasets.GeneratorBasedBuilder):
"""This is Kinyarwanda and Kirundi news dataset called KINNEWS and KIRNEWS."""
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="kinnews_raw", description="Dataset for Kinyarwanda language"),
datasets.BuilderConfig(name="kinnews_cleaned", description="Cleaned dataset for Kinyarwanda language"),
datasets.BuilderConfig(name="kirnews_raw", description="Dataset for Kirundi language"),
datasets.BuilderConfig(name="kirnews_cleaned", description="Cleaned dataset for Kirundi language"),
]
class_labels = [
"politics",
"sport",
"economy",
"health",
"entertainment",
"history",
"technology",
"tourism",
"culture",
"fashion",
"religion",
"environment",
"education",
"relationship",
]
label_columns = {"kinnews_raw": "kin_label", "kirnews_raw": "kir_label"}
def _info(self):
if "raw" in self.config.name:
features = datasets.Features(
{
"label": datasets.ClassLabel(names=self.class_labels),
self.label_columns[self.config.name]: datasets.Value("string"),
"en_label": datasets.Value("string"),
"url": datasets.Value("string"),
"title": datasets.Value("string"),
"content": datasets.Value("string"),
}
)
else:
features = datasets.Features(
{
"label": datasets.ClassLabel(names=self.class_labels),
"title": datasets.Value("string"),
"content": 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."""
lang, kind = self.config.name.split("_")
data_dir = dl_manager.download_and_extract(_URLs[lang])
lang_dir = lang.upper()
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, lang_dir, kind, "train.csv"),
"split": "train",
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={"filepath": os.path.join(data_dir, lang_dir, kind, "test.csv"), "split": "test"},
),
]
def _generate_examples(self, filepath, split):
"""Yields examples."""
with open(filepath, encoding="utf-8") as csv_file:
csv_reader = csv.reader(
csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
)
next(csv_reader)
for id_, row in enumerate(csv_reader):
if "raw" in self.config.name:
label, k_label, en_label, url, title, content = row
yield id_, {
"label": self.class_labels[int(label) - 1],
self.label_columns[self.config.name]: k_label,
"en_label": en_label,
"url": url,
"title": title,
"content": content,
}
else:
label, title, content = row
yield id_, {
"label": self.class_labels[int(label) - 1],
"title": title,
"content": content,
}
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