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# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the 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
"""ParaCrawl (Bitextor) parallel open-source machine translation benchmark."""
import collections
import datasets
_DESCRIPTION = "Web-Scale Parallel Corpora for Official European Languages."
_BENCHMARK_URL = "https://paracrawl.eu/releases.html"
_CITATION = """\
@misc {paracrawl,
title = {ParaCrawl},
year = {2018},
url = {http://paracrawl.eu/download.html.}
}
"""
_BASE_DATA_URL_FORMAT_STR = (
"https://s3.amazonaws.com/web-language-models/" "paracrawl/release4/en-{target_lang}.bicleaner07." "txt.gz"
)
def _target_languages():
"""Create the sorted dictionary of language codes, and language names.
Returns:
The sorted dictionary as an instance of `collections.OrderedDict`.
"""
langs = {
"bg": "Bulgarian",
"cs": "Czech",
"da": "Danish",
"de": "German",
"el": "Greek",
"es": "Spanish",
"et": "Estonian",
"fi": "Finnish",
"fr": "French",
"ga": "Irish",
"hr": "Croatian",
"hu": "Hungarian",
"it": "Italian",
"lt": "Lithuanian",
"lv": "Latvian",
"mt": "Maltese",
"nl": "Dutch",
"pl": "Polish",
"pt": "Portuguese",
"ro": "Romanian",
"sk": "Slovak",
"sl": "Slovenian",
"sv": "Swedish",
}
return collections.OrderedDict(sorted(langs.items()))
class ParaCrawlConfig(datasets.BuilderConfig):
"""BuilderConfig for ParaCrawl."""
def __init__(self, target_language=None, **kwargs):
"""BuilderConfig for ParaCrawl.
Args:
for the `datasets.features.text.TextEncoder` used for the features feature.
target_language: Target language that will be used to translate to from
English which is always the source language. It has to contain 2-letter
coded strings. For example: "se", "hu".
**kwargs: Keyword arguments forwarded to super.
"""
# Validate the target language.
if target_language not in _target_languages():
raise ValueError("Invalid target language: %s " % target_language)
# Initialize the base class.
name = "en%s" % (target_language)
description = ("Translation dataset from English to %s.") % (target_language)
super(ParaCrawlConfig, self).__init__(name=name, description=description, **kwargs)
# Store the attributes.
self.target_language = target_language
self.data_url = _BASE_DATA_URL_FORMAT_STR.format(target_lang=target_language)
class ParaCrawl(datasets.GeneratorBasedBuilder):
"""ParaCrawl machine translation dataset."""
# Version history:
# 1.0.0: S3 (new shuffling, sharding and slicing mechanism).
# 0.1.0: Initial version.
BUILDER_CONFIGS = [
# The version below does not refer to the version of the released
# database. It only indicates the version of the TFDS integration.
ParaCrawlConfig( # pylint: disable=g-complex-comprehension
target_language=target_language,
version=datasets.Version("1.0.0"),
)
for target_language in _target_languages()
]
def _info(self):
target_language = self.config.target_language
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{"translation": datasets.features.Translation(languages=("en", target_language))}
),
supervised_keys=("en", target_language),
homepage=_BENCHMARK_URL,
citation=_CITATION,
)
def _vocab_text_gen(self, files, language):
for _, ex in self._generate_examples(**files):
yield ex[language]
def _split_generators(self, dl_manager):
# Download the data file.
data_file = dl_manager.download_and_extract({"data_file": self.config.data_url})
# Return the single split of the data.
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs=data_file)]
def _generate_examples(self, data_file):
"""This function returns the examples in the raw (text) form."""
target_language = self.config.target_language
with open(data_file, encoding="utf-8") as f:
for idx, line in enumerate(f):
line_parts = line.strip().split("\t")
if len(line_parts) != 2:
msg = (
"Wrong data format in line {}. The line '{}' does " "not have exactly one delimiter."
).format(idx, line)
raise ValueError(msg)
source, target = line_parts[0].strip(), line_parts[1].strip()
yield idx, {"translation": {"en": source, target_language: target}}
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