import datasets from huggingface_hub.file_download import hf_hub_url import glob import json import pandas as pd try: import lzma as xz except ImportError: import pylzma as xz datasets.logging.set_verbosity_info() logger = datasets.logging.get_logger(__name__) _DESCRIPTION ="""\ """ _HOMEPAGE = "" _LICENSE = "" _CITATION = "" _URL = { 'data/' } _LANGUAGES = [ "fr","it","es","en","de","pt" ] _TYPES = [ "laws", "judgements" ] _SOURCES = [ "MultiLegalPile", "Wipolex", "Jug", "BVA", "CC", "IP", "SCOTUS", "SwissJudgementPrediction" "Gesetz", "Constitution", "CivilCode", "CriminalCode", ] """ see https://huggingface.co/datasets/joelito/MultiLegalPile_Wikipedia_Filtered/blob/main/MultiLegalPile_Wikipedia_Filtered.py """ _HIGHEST_NUMBER_OF_SHARDS = 4 class MultilingualSBDConfig(datasets.BuilderConfig): def __init__(self, name:str, **kwargs): super( MultilingualSBDConfig, self).__init__(**kwargs) self.name = name self.language = name.split("_")[0] self.type = name.split("_")[1] #self.source = name.split("_")[2] class MultilingualSBD(datasets.GeneratorBasedBuilder): BUILDER_CONFIG_CLASS = MultilingualSBDConfig BUILDER_CONFIGS = [ MultilingualSBDConfig(f"{language}_{type}") for language in _LANGUAGES + ['all'] for type in _TYPES + ["all"] ] DEFAULT_CONFIG_NAME = 'all_all' def _info(self): features = datasets.Features( { "text": datasets.Value("string"), "spans": [ { "start": datasets.Value("int64"), "end": datasets.Value("int64"), "label": datasets.Value("string"), "token_start": datasets.Value("int64"), "token_end": datasets.Value("int64") } ], "tokens": [ { "text": datasets.Value("string"), "start": datasets.Value("int64"), "end": datasets.Value("int64"), "id": datasets.Value("int64"), "ws": datasets.Value("bool") } ], "source": datasets.Value("string") } ) return datasets.DatasetInfo( description=_DESCRIPTION, features = features, homepage = _HOMEPAGE, citation=_CITATION ) def _split_generators(self, dl_manager): def download_url(filename): url = hf_hub_url( repo_id="tbrugger/Multilingual-SBD", filename = f'data/{filename}.jsonl.xz', repo_type='dataset' ) return dl_manager.download(url) languages = _LANGUAGES if self.config.language == "all" else [self.config.language] types = _TYPES if self.config.type == 'all' else [self.config.type] split_generators = [] for split in [datasets.Split.TRAIN]: filepaths = [] for language in languages: for type in types: for shard in range(_HIGHEST_NUMBER_OF_SHARDS): try: filepaths.append(download_url(f'{language}_{type}_{shard}')) except: break split_generators.append( datasets.SplitGenerator(name=split, gen_kwargs={'filepaths': filepaths}) ) return split_generators def _generate_examples(self,filepaths): id_ = 0 for filepath in filepaths: if filepath: logger.info("Generating examples from = %s", filepath) try: with xz.open(open(filepath,'rb'), 'rt', encoding='utf-8') as f: json_list = list(f) for json_str in json_list: example = json.loads(json_str) if id_ == 0: print(example) if example is not None and isinstance(example, dict): yield id_, example id_ +=1 except Exception: logger.exception("Error while processing file %s", filepath)