# coding=utf-8 # Copyright 2020 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. """Cleaned Indonesian split of the KoPI corpus.""" import json import glob import gzip from posixpath import split import textwrap import datasets import zstandard as zstd logger = datasets.logging.get_logger(__name__) _CITATION = """ """ _DESCRIPTION = """\ """ _TYPE = ['raw','dedup','neardup'] _CONF_LANG = ['ace_Latn','ban_Latn','bjn_Latn','ind_Latn','jav_Latn','min_Latn','sun_Latn'] _CONFIGS = [] for j in _CONF_LANG: for m in _TYPE: _CONFIGS.append(j+'-'+m) _ALL_CONFIG = ["all-raw", "all-dedup", "all-neardup"] + _CONFIGS _HOMEPAGE = "https://huggingface.co/datasets/munggok/KoPI-NLLB" _LICENSE = "ODC_C" _BASE_URL = 'https://huggingface.co/datasets/munggok/KoPI-NLLB/resolve/main/{tipe}/{lang}.json.zst' def kopi_nllb_constructor(nam): return KoPINLLBConfig( name=nam, version=datasets.Version("1.0.0"), ) class KoPINLLBConfig(datasets.BuilderConfig): """BuilderConfig for the Clean KoPI corpus.""" def __init__(self, **kwargs): """BuilderConfig for Clean KoPI corpus. Args: **kwargs: keyword arguments forwarded to super. """ super().__init__(**kwargs) class KoPINLLB(datasets.GeneratorBasedBuilder): """KoPI corpus.""" BUILDER_CONFIGS = [kopi_nllb_constructor(m) for m in _ALL_CONFIG ] def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "text": datasets.Value("string"), "url": datasets.Value("string"), "score": datasets.Value("float32"), "source": datasets.Value("string"), } ), supervised_keys=None, homepage=_HOMEPAGE, license=_LICENSE, citation=_CITATION, ) def _split_generators(self, dl_manager): name = self.config.name.split("-") if name[0] == "all": train = [_BASE_URL.format(tipe=name[1],lang=m) for m in _CONF_LANG] else: train = [_BASE_URL.format(tipe=name[1],lang=name[0])] train_downloaded_files = dl_manager.download(train) return [ datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}) ] def _generate_examples(self, filepaths): """This function returns the examples in the raw (text) form by iterating on all the files.""" id_ = 0 for filepath in filepaths: logger.info(f"Generating examples from {filepath}") with zstd.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: for line in f: if line: example = json.loads(line) if line: example = json.loads(line) yield id_, {'text':example['text'],'url':example['url'],'source':example['source'],'score': float(example['score'])} id_ += 1