# coding=utf-8 # Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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. import os from pathlib import Path from typing import Dict, List, Tuple import datasets from seacrowd.utils import schemas from seacrowd.utils.configs import SEACrowdConfig from seacrowd.utils.constants import TASK_TO_SCHEMA, Licenses, Tasks _CITATION = """\ @misc{nomoto2018melayustandardlisan, author = {Hiroki Nomoto}, title = {Korpus Variasi Bahasa Melayu: Standard Lisan}, year = {2018}, url = {https://github.com/matbahasa/Melayu_Standard_Lisan} } """ _DATASETNAME = "melayu_standard_lisan" _DESCRIPTION = """\ Korpus Variasi Bahasa Melayu: Standard Lisan is a language corpus sourced from monologues of various melayu folklores. """ _HOMEPAGE = "https://github.com/matbahasa/Melayu_Standard_Lisan" _LANGUAGES = ["zlm"] _LICENSE = Licenses.CC_BY_4_0.value _LOCAL = False _URLS = { "kl201701": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201701.txt", "kl201702": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201702.txt", "kl201703": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201703.txt", "kl201704": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201704.txt", "kl201705": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201705.txt", "kl201706": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201706.txt", "kl201707": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201707.txt", "kl201708": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201708.txt", "kl201709": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201709.txt", "kl201710": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201710.txt", "kl201711": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201711.txt", "kl201712": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201712.txt", "kl201713": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201713.txt", "kl201714": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201714.txt", "kl201715": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201715.txt", "kl201716": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201716.txt", "kl201717": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201717.txt", "kl201718": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201718.txt", "kl201719": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201719.txt", "kl201720": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201720.txt", "kl201721": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201721.txt", "kl201722": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201722.txt", "kl201723": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201723.txt", "kl201724": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201724.txt", "kl201725": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201725.txt", "kl201726": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201726.txt", "kl201727": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201727.txt", "kl201728": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201728.txt", "kl201729": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201729.txt", "kl201730": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201730.txt", "kl201731": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201731.txt", "kl201732": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201732.txt", "kl201733": "https://raw.githubusercontent.com/matbahasa/Melayu_Standard_Lisan/master/KL201733.txt", } _SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING] _SOURCE_VERSION = "1.0.0" _SEACROWD_VERSION = "2024.06.20" class MelayuStandardLisan(datasets.GeneratorBasedBuilder): """Korpus Variasi Bahasa Melayu: Standard Lisan is a language corpus sourced from monologues of various melayu folklores.""" SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) SEACROWD_SCHEMA_NAME = TASK_TO_SCHEMA[_SUPPORTED_TASKS[0]].lower() BUILDER_CONFIGS = [ SEACrowdConfig( name=f"{_DATASETNAME}_source", version=SOURCE_VERSION, description=f"{_DATASETNAME} source schema", schema="source", subset_id=f"{_DATASETNAME}", ), SEACrowdConfig( name=f"{_DATASETNAME}_seacrowd_{SEACROWD_SCHEMA_NAME}", version=SEACROWD_VERSION, description=f"{_DATASETNAME} SEACrowd schema", schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}", subset_id=f"{_DATASETNAME}", ), ] DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source" def _info(self) -> datasets.DatasetInfo: if self.config.schema == "source": features = datasets.Features( { "id": datasets.Value("string"), "text": datasets.Value("string"), } ) elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}": features = schemas.self_supervised_pretraining.features return datasets.DatasetInfo( description=_DESCRIPTION, features=features, homepage=_HOMEPAGE, license=_LICENSE ) def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: """Returns SplitGenerators.""" urls = [_URLS[key] for key in _URLS.keys()] data_path = dl_manager.download_and_extract(urls) return [ datasets.SplitGenerator( name=datasets.Split.TRAIN, gen_kwargs={"filepath": data_path[0], "split": "train", "other_path": data_path[1:]}, ) ] def _generate_examples(self, filepath: Path, split: str, other_path: List) -> Tuple[int, Dict]: """Yields examples as (key, example) tuples.""" filepaths = [filepath] + other_path data = [] for filepath in filepaths: with open(filepath, "r") as f: data.append(" ".join([line.rstrip() for line in f.readlines()])) for id, text in enumerate(data): yield id, {"id": id, "text": text}