Datasets:
Tasks:
Translation
Multilinguality:
multilingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
ArXiv:
Tags:
DOI:
License:
File size: 3,077 Bytes
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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
"""Faroese-Danish parallel corpus from ITU Copenhagen"""
import os
import datasets
logger = datasets.logging.get_logger(__name__)
_CITATION = """\
"""
_DESCRIPTION = """\
"""
_URL = "itu_fo_da_monolithic.tsv"
class ItuFaroeseDanishConfig(datasets.BuilderConfig):
"""BuilderConfig for ItuFaroeseDanish"""
def __init__(self, **kwargs):
"""BuilderConfig ItuFaroeseDanish.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(ItuFaroeseDanishConfig, self).__init__(**kwargs)
class ItuFaroeseDanish(datasets.GeneratorBasedBuilder):
"""ItuFaroeseDanish dataset."""
BUILDER_CONFIGS = [
ItuFaroeseDanishConfig(name="ItuFaroeseDanish", version=datasets.Version("1.0.0"), description="Faroese-Danish parallel text from ITU Copenhagen"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"id": datasets.Value("string"),
"origin": datasets.Value("string"),
"fo": datasets.Value("string"),
"da": datasets.Value("string"),
}
),
supervised_keys=None,
homepage="",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
downloaded_file = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
]
def _generate_examples(self, filepath):
logger.info("⏳ Generating examples from = %s", filepath)
texts = {"fao":{}, "dan":{}}
with open(filepath, encoding="utf-8") as f:
for line in f:
line = line.strip()
if line:
code, text = line.split("\t")
origin, language = code.split("_")
texts[language][origin] = text
if texts["fao"].keys() != texts["dan"].keys():
raise ValueError("Faroese and Danish keys don't match")
guid = 0
for origin in texts["fao"]:
yield guid, {
"id": str(guid),
"origin": origin,
"fo": texts["fao"][origin],
"da": texts["dan"][origin],
}
guid += 1
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