Datasets:
Tasks:
Translation
Multilinguality:
translation
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
found
Source Datasets:
original
Tags:
License:
# 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. | |
"""XhosaNavy English -Xhosa""" | |
import os | |
import datasets | |
_CITATION = """\ | |
J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International \ | |
Conference on Language Resources and Evaluation (LREC 2012)""" | |
_HOMEPAGE = "http://opus.nlpl.eu/XhosaNavy-v1.php" | |
_LICENSE = "" | |
_DESCRIPTION = """\ | |
This dataset is designed for machine translation from English to Xhosa.""" | |
_URLs = {"train": "https://object.pouta.csc.fi/OPUS-XhosaNavy/v1/moses/en-xh.txt.zip"} | |
class OpusXhosanavy(datasets.GeneratorBasedBuilder): | |
VERSION = datasets.Version("1.0.0") | |
BUILDER_CONFIGS = [datasets.BuilderConfig(name="en-xh", version=VERSION, description="XhosaNavy English -Xhosa")] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=_DESCRIPTION, | |
features=datasets.Features( | |
{"translation": datasets.features.Translation(languages=tuple(self.config.name.split("-")))} | |
), | |
supervised_keys=None, | |
homepage="http://opus.nlpl.eu/XhosaNavy-v1.php", | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
"""Returns SplitGenerators.""" | |
data_dir = dl_manager.download_and_extract(_URLs) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"source_file": os.path.join(data_dir["train"], "XhosaNavy.en-xh.en"), | |
"target_file": os.path.join(data_dir["train"], "XhosaNavy.en-xh.xh"), | |
"split": "train", | |
}, | |
), | |
] | |
def _generate_examples(self, source_file, target_file, split): | |
"""This function returns the examples in the raw (text) form.""" | |
with open(source_file, encoding="utf-8") as f: | |
source_sentences = f.read().split("\n") | |
with open(target_file, encoding="utf-8") as f: | |
target_sentences = f.read().split("\n") | |
assert len(target_sentences) == len(source_sentences), "Sizes do not match: %d vs %d for %s vs %s." % ( | |
len(source_sentences), | |
len(target_sentences), | |
source_file, | |
target_file, | |
) | |
source, target = tuple(self.config.name.split("-")) | |
for idx, (l1, l2) in enumerate(zip(source_sentences, target_sentences)): | |
result = {"translation": {source: l1, target: l2}} | |
yield idx, result | |