tatoeba.py

# 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
from itertools import combinations
import os

import datasets


_DESCRIPTION = """\
This is a collection of translated sentences from Tatoeba
397 languages, 4,344 bitexts
total number of files: 1,572
total number of tokens: 86.26M
total number of sentence fragments: 11.80M
"""
_HOMEPAGE_URL = "http://opus.nlpl.eu/Tatoeba.php"
_CITATION = """\
@InProceedings{TIEDEMANN12.463,
  author = {J{\"o}rg}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 = "2023.04.12"  # "2021.7.22"
_DATE = "v" + "-".join(s.zfill(2) for s in _VERSION.split("."))
_BASE_NAME = "Tatoeba.{}.{}"
_BASE_URL = "https://opus.nlpl.eu/download.php?f=Tatoeba/{}/moses/{}-{}.txt.zip"
_LANGUAGES = ["ab", "acm", "ady", "af", "afb", "afh", "aii", "ain", "ajp", "akl",
              "aln", "alt", "am", "an", "ang", "aoz", "apc", "ar", "arq", "ary",
              "arz", "as", "ast", "av", "avk", "awa", "ayl", "az", "ba", "bal",
              "ban", "bar", "be", "ber", "bg", "bho", "bjn", "bm", "bn", "bo",
              "bom", "br", "brx", "bs", "bua", "bvy", "bzt", "ca", "cay", "cbk",
              "ce", "ceb", "ch", "chg", "chn", "cho", "chr", "cjy", "ckb", "ckt",
              "cmn", "co", "cpi", "crh", "crk", "crs", "cs", "csb", "cv", "cy",
              "cycl", "da", "de", "diq", "dng", "drt", "dsb", "dtp", "dv", "dws",
              "ee", "egl", "el", "emx", "en", "enm", "eo", "es", "et", "eu", "evn",
              "ext", "fi", "fj", "fkv", "fo", "fr", "frm", "fro", "frr", "fuc",
              "fur", "fuv", "fy", "ga", "gag", "gan", "gbm", "gcf", "gd", "gil",
              "gl", "gn", "gom", "gos", "got", "grc", "gsw", "gu", "guc", "gv",
              "ha", "hak", "haw", "hbo", "he", "hi", "hif", "hil", "hnj", "hoc",
              "hr", "hrx", "hsb", "hsn", "ht", "hu", "hy", "ia", "iba", "id",
              "ie", "ig", "igs", "ii", "ike", "ilo", "io", "is", "it", "izh",
              "ja", "jam", "jbo", "jdt", "jpa", "jv", "ka", "kaa", "kab", "kam",
              "kbd", "kek", "kha", "kiu", "kjh", "kk", "kl", "klj", "km", "kmr",
              "kn", "knc", "ko", "koi", "kpv", "krc", "krl", "ksh", "ku", "kum",
              "kw", "kxi", "ky", "kzj", "la", "laa", "lad", "lb", "ldn", "lfn",
              "lg", "li", "lij", "liv", "lkt", "lld", "lmo", "ln", "lo", "lou",
              "lt", "ltg", "lut", "lv", "lzh", "lzz", "mad", "mai", "max", "mdf",
              "mfa", "mfe", "mg", "mgm", "mh", "mhr", "mi", "mic", "mik", "min",
              "mk", "ml", "mn", "mnc", "mni", "mnr", "mnw", "moh", "mr", "mt",
              "mus", "mvv", "mwl", "mww", "my", "myv", "na", "nah", "nan", "nap",
              "nb", "nch", "nds", "ngt", "ngu", "niu", "nl", "nlv", "nn", "nnb",
              "nog", "non", "nov", "npi", "nst", "nus", "nv", "ny", "nys", "oar",
              "oc", "ofs", "oj", "ood", "or", "orv", "os", "osp", "ota", "otk",
              "pa", "pag", "pal", "pam", "pap", "pau", "pcd", "pdc", "pes", "phn",
              "pi", "pl", "pms", "pnb", "ppl", "prg", "ps", "pt", "qu", "quc",
              "qxq", "qya", "rap", "rhg", "rif", "rm", "rn", "ro", "rom", "ru",
              "rue", "rw", "ryu", "sa", "sah", "sat", "sc", "scn", "sco", "sd",
              "sdh", "se", "sg", "sgs", "shi", "shs", "shy", "si", "sjn", "skr",
              "sl", "sm", "sma", "sn", "so", "sq", "sr", "srn", "stq", "su",
              "sux", "sv", "swc", "swg", "swh", "syc", "syl", "szl", "ta", "te",
              "tet", "tg", "th", "thv", "ti", "tig", "tk", "tkl", "tl", "tlh",
              "tly", "tmr", "tmw", "tn", "to", "toi", "tok", "toki", "tpi", "tpw",
              "tr", "ts", "tt", "tts", "tvl", "ty", "tyv", "tzl", "udm", "ug",
              "uk", "umb", "ur", "uz", "vec", "vep", "vi", "vo", "vro", "wa",
              "war", "wo", "wuu", "xal", "xh", "xmf", "xqa", "yi", "yo", "yue",
              "zea", "zgh", "zlm", "zsm", "zu", "zza"]
_LANGUAGE_PAIRS = list(combinations(_LANGUAGES, 2))


class TatoebaConfig(datasets.BuilderConfig):
    def __init__(self, *args, lang1=None, lang2=None, date=_DATE, **kwargs):
        super().__init__(
            *args,
            name=f"{lang1}-{lang2}",
            **kwargs,
        )
        self.lang1 = lang1
        self.lang2 = lang2
        self.date = date


class Tatoeba(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        TatoebaConfig(
            lang1=lang1,
            lang2=lang2,
            description=f"Translating {lang1} to {lang2} or vice versa",
            version=datasets.Version(_VERSION),
        )
        for lang1, lang2 in _LANGUAGE_PAIRS
    ]
    BUILDER_CONFIG_CLASS = TatoebaConfig

    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):
        def _base_url(lang1, lang2, date):
            return _BASE_URL.format(date, lang1, lang2)

        download_url = _base_url(self.config.lang1, self.config.lang2, self.config.date)
        path = dl_manager.download_and_extract(download_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