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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.
"""The Large Spanish Corpus is a compilation of Spanish corpora spanning Wikipedia to European parliament notes."""
import os
import datasets
_CITATION = """\
@dataset{jose_canete_2019_3247731,
author = {José Cañete},
title = {Compilation of Large Spanish Unannotated Corpora},
month = may,
year = 2019,
publisher = {Zenodo},
doi = {10.5281/zenodo.3247731},
url = {https://doi.org/10.5281/zenodo.3247731}
}
"""
_DESCRIPTION = """\
The Large Spanish Corpus is a compilation of 15 unlabelled Spanish corpora spanning Wikipedia to European parliament \
notes. Each config contains the data corresponding to a different corpus. For example, "all_wiki" only includes \
examples from Spanish Wikipedia. By default, the config is set to "combined" which loads all the corpora; with this \
setting you can also specify the number of samples to return per corpus by configuring the "split" argument.
"""
_HOMEPAGE = "https://github.com/josecannete/spanish-corpora"
_LICENSE = "MIT"
_URL = "data/raw.zip"
_CORPORA = [
"JRC",
"EMEA",
"GlobalVoices",
"ECB",
"DOGC",
"all_wikis",
"TED",
"multiUN",
"Europarl",
"NewsCommentary11",
"UN",
"EUBookShop",
"ParaCrawl",
"OpenSubtitles2018",
"DGT",
]
_CORPORA_FILEPATHS = {corpus: os.path.join("spanish-corpora", "raw", f"{corpus}.txt") for corpus in _CORPORA}
_VERSION = "1.1.0"
_COMBINED = "combined"
class LargeSpanishCorpusConfig(datasets.BuilderConfig):
def __init__(self, corpora=None, **kwargs):
super(LargeSpanishCorpusConfig, self).__init__(version=datasets.Version(_VERSION, ""), **kwargs)
self.corpora = corpora
@property
def filepaths(self):
return [_CORPORA_FILEPATHS[corpus] for corpus in self.corpora]
class LargeSpanishCorpus(datasets.GeneratorBasedBuilder):
"""The Large Spanish Corpus."""
BUILDER_CONFIGS = [
LargeSpanishCorpusConfig(name=corpus, corpora=[corpus], description=f"Spanish examples in corpus {corpus}.")
for corpus in _CORPORA
] + [
LargeSpanishCorpusConfig(
name=_COMBINED, corpora=_CORPORA, description="Complete Spanish dataset with all corpora."
)
]
BUILDER_CONFIG_CLASS = LargeSpanishCorpusConfig
DEFAULT_CONFIG_NAME = _COMBINED
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"text": datasets.Value("string"),
}
),
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
data_dir = dl_manager.download_and_extract(_URL)
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"data_dir": data_dir})]
def _generate_examples(self, data_dir):
_id = 0
for filepath in self.config.filepaths:
filepath = os.path.join(data_dir, filepath)
with open(filepath, mode="r", encoding="utf-8") as f:
for line in f:
yield _id, {"text": line.strip()},
_id += 1
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