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| from typing import Dict, List, Tuple |
|
|
| import datasets |
|
|
| from seacrowd.utils import schemas |
| from seacrowd.utils.configs import SEACrowdConfig |
| from seacrowd.utils.constants import Licenses, Tasks |
|
|
| |
| _CITATION = """\ |
| @article{, |
| author = {}, |
| title = {}, |
| journal = {}, |
| volume = {}, |
| year = {}, |
| url = {}, |
| doi = {}, |
| biburl = {}, |
| bibsource = {} |
| } |
| """ |
|
|
| _LOCAL = False |
| _LANGUAGES = ["mya", "ceb", "gor", "hil", "ilo", "ind", "jav", "khm", "lao", "zlm", "nia", "tgl", "tha", "vie"] |
|
|
| _DATASETNAME = "mozilla_pontoon" |
| _DESCRIPTION = """ |
| This dataset contains crowdsource translations of more than 200 languages for |
| different Mozilla open-source projects from Mozilla's Pontoon localization platform. |
| Source sentences are in English. |
| """ |
|
|
| _HOMEPAGE = "https://huggingface.co/datasets/ayymen/Pontoon-Translations" |
| _LICENSE = Licenses.BSD_3_CLAUSE.value |
| _URL = "https://huggingface.co/datasets/ayymen/Pontoon-Translations" |
|
|
| _SUPPORTED_TASKS = [Tasks.MACHINE_TRANSLATION] |
| _SOURCE_VERSION = "1.0.0" |
| _SEACROWD_VERSION = "2024.06.20" |
|
|
|
|
| class MozillaPontoonDataset(datasets.GeneratorBasedBuilder): |
| """Dataset of translations from Mozilla's Pontoon platform.""" |
|
|
| |
| |
| LANG_CODE_MAPPER = {"mya": "my", "ceb": "ceb", "gor": "gor", "hil": "hil", "ilo": "ilo", "ind": "id", "jav": "jv", "khm": "km", "lao": "lo", "zlm": "ms", "nia": "nia", "tgl": "tl", "tha": "th", "vie": "vi"} |
|
|
| |
| BUILDER_CONFIGS = [ |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_eng_{lang}_source", |
| version=datasets.Version(_SOURCE_VERSION), |
| description=f"{_DATASETNAME} source schema for {lang} language", |
| schema="source", |
| subset_id=f"{_DATASETNAME}_eng_{lang}", |
| ) |
| for lang in _LANGUAGES |
| ] + [ |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_eng_{lang}_seacrowd_t2t", |
| version=datasets.Version(_SEACROWD_VERSION), |
| description=f"{_DATASETNAME} SEACrowd schema for {lang} language", |
| schema="seacrowd_t2t", |
| subset_id=f"{_DATASETNAME}_eng_{lang}", |
| ) |
| for lang in _LANGUAGES |
| ] |
|
|
| |
| BUILDER_CONFIGS.extend( |
| [ |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_source", |
| version=datasets.Version(_SOURCE_VERSION), |
| description=f"{_DATASETNAME} source schema for all languages", |
| schema="source", |
| subset_id=_DATASETNAME, |
| ), |
| SEACrowdConfig( |
| name=f"{_DATASETNAME}_seacrowd_t2t", |
| version=datasets.Version(_SEACROWD_VERSION), |
| description=f"{_DATASETNAME} SEACrowd schema for all languages", |
| schema="seacrowd_t2t", |
| subset_id=_DATASETNAME, |
| ), |
| ] |
| ) |
|
|
| DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" |
|
|
| def _info(self) -> datasets.DatasetInfo: |
| if self.config.schema == "source": |
| features = datasets.Features( |
| { |
| "source_string": datasets.Value("string"), |
| "target_string": datasets.Value("string"), |
| } |
| ) |
| elif self.config.schema == "seacrowd_t2t": |
| features = schemas.text2text_features |
|
|
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=features, |
| homepage=_HOMEPAGE, |
| license=_LICENSE, |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
| """Returns SplitGenerators.""" |
| |
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, |
| gen_kwargs={"split": "train"}, |
| ), |
| ] |
|
|
| def _load_hf_data_from_remote(self, language: str) -> datasets.DatasetDict: |
| """Load dataset from HuggingFace.""" |
| hf_lang_code = self.LANG_CODE_MAPPER[language] |
| hf_remote_ref = "/".join(_URL.split("/")[-2:]) |
| return datasets.load_dataset(hf_remote_ref, f"en-{hf_lang_code}", split="train") |
|
|
| def _generate_examples(self, split: str) -> Tuple[int, Dict]: |
| """Yields examples as (key, example) tuples.""" |
| languages = [] |
| pontoon_datasets = [] |
|
|
| lang = self.config.subset_id.split("_")[-1] |
| if lang in _LANGUAGES: |
| languages.append(lang) |
| pontoon_datasets.append(self._load_hf_data_from_remote(lang)) |
| else: |
| for lang in _LANGUAGES: |
| languages.append(lang) |
| pontoon_datasets.append(self._load_hf_data_from_remote(lang)) |
|
|
| index = 0 |
| for lang, lang_subset in zip(languages, pontoon_datasets): |
| for row in lang_subset: |
| if self.config.schema == "source": |
| example = row |
|
|
| elif self.config.schema == "seacrowd_t2t": |
| example = { |
| "id": str(index), |
| "text_1": row["source_string"], |
| "text_2": row["target_string"], |
| "text_1_name": "eng", |
| "text_2_name": lang, |
| } |
| yield index, example |
| index += 1 |
|
|