Datasets:

Multilinguality:
multilingual
Size Categories:
10M<n<100M
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
giga_fren / giga_fren.py
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Update files from the datasets library (from 1.5.0)
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# coding=utf-8
# Copyright 2020 HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
import os
import datasets
_DESCRIPTION = """\
Giga-word corpus for French-English from WMT2010 collected by Chris Callison-Burch
2 languages, total number of files: 452
total number of tokens: 1.43G
total number of sentence fragments: 47.55M
"""
_HOMEPAGE_URL = "http://opus.nlpl.eu/giga-fren.php"
_CITATION = """\
@InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Thierry Declerck and Mehmet Ugur Dogan and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis},
publisher = {European Language Resources Association (ELRA)},
isbn = {978-2-9517408-7-7},
language = {english}
}
"""
_VERSION = "2.0.0"
_BASE_NAME = "giga-fren.{}.{}"
_URL = "https://object.pouta.csc.fi/OPUS-giga-fren/v2/moses/en-fr.txt.zip"
class GigaFrenConfig(datasets.BuilderConfig):
def __init__(self, *args, **kwargs):
super().__init__(
*args,
name="en-fr",
**kwargs,
)
@property
def lang1(self):
return "en"
@property
def lang2(self):
return "fr"
class GigaFren(datasets.GeneratorBasedBuilder):
BUILDER_CONFIGS = [GigaFrenConfig(description="Translating en to fr ", version=datasets.Version(_VERSION))]
BUILDER_CONFIG_CLASS = GigaFrenConfig
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"translation": datasets.Translation(languages=(self.config.lang1, self.config.lang2)),
},
),
supervised_keys=None,
homepage=_HOMEPAGE_URL,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
path = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"datapath": path},
)
]
def _generate_examples(self, datapath):
l1, l2 = self.config.lang1, self.config.lang2
folder = l1 + "-" + l2
l1_file = _BASE_NAME.format(folder, l1)
l2_file = _BASE_NAME.format(folder, l2)
l1_path = os.path.join(datapath, l1_file)
l2_path = os.path.join(datapath, l2_file)
with open(l1_path, encoding="utf-8") as f1, open(l2_path, encoding="utf-8") as f2:
for sentence_counter, (x, y) in enumerate(zip(f1, f2)):
x = x.strip()
y = y.strip()
result = (
sentence_counter,
{
"id": str(sentence_counter),
"translation": {l1: x, l2: y},
},
)
yield result