giga_fren.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
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# 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=f"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