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"""Legal MC4""" |
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import ast |
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import json |
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import datasets |
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from huggingface_hub.file_download import hf_hub_url |
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try: |
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import lzma as xz |
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except ImportError: |
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import pylzma as xz |
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datasets.logging.set_verbosity_info() |
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logger = datasets.logging.get_logger(__name__) |
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_DESCRIPTION = """ |
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Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages |
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""" |
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_CITATION = """ |
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""" |
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_REPO_ID = "joelito/legal-mc4" |
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_URL = f"https://huggingface.co/datasets/{_REPO_ID}" |
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_LANGUAGES = { |
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"bg": 0, |
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"cs": 2, |
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"da": 0, |
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"de": 8, |
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"el": 0, |
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"en": 1, |
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"es": 9, |
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"et": 0, |
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"fi": 0, |
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"fr": 2, |
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"ga": 0, |
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"hu": 0, |
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"it": 3, |
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"lt": 0, |
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"lv": 0, |
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"mt": 0, |
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"nl": 0, |
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"pl": 2, |
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"pt": 1, |
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"ro": 0, |
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"sk": 0, |
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"sl": 0, |
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"sv": 0, |
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} |
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_LANGS = list(_LANGUAGES.keys()) |
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class LegalMC4Config(datasets.BuilderConfig): |
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"""BuilderConfig for Legal-MC4.""" |
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def __init__(self, name: str, **kwargs): |
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"""BuilderConfig for Legal-MC4. |
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Args: |
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name: One of bg,cs,da,de,el,en,es,et,fi,fr,ga,hu,it,lt,lv,mt,nl,pl,pt,ro,sk,sl,sv or all |
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**kwargs: keyword arguments forwarded to super. |
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""" |
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super(LegalMC4Config, self).__init__(**kwargs) |
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self.name = name |
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class MC4Legal(datasets.GeneratorBasedBuilder): |
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"""Legal-MC4: A Corpus Covering the Legal Part of MC4 for European Languages""" |
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BUILDER_CONFIGS = [LegalMC4Config(language) for language in _LANGS + ["all"]] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"url": datasets.Value("string"), |
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"timestamp": datasets.Value("timestamp[s]"), |
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"matches": datasets.Sequence(datasets.Value("string")), |
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"text": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage=_URL, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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def get_url(file_name): |
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return hf_hub_url(repo_id=_REPO_ID, filename=f"data/{file_name}.jsonl.xz", repo_type="dataset") |
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data_urls = [] |
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languages = _LANGS if self.config.name == "all" else [self.config.name] |
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split_generators = [] |
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for split in [datasets.Split.TRAIN, datasets.Split.VALIDATION]: |
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for language in languages: |
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shards = range(_LANGUAGES[language] + 1) if split == datasets.Split.TRAIN else [0] |
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for shard in shards: |
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data_urls.append(get_url(f"{language}.{str(split)}.{shard}")) |
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downloaded_files = dl_manager.download(data_urls) |
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split_generators.append( |
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datasets.SplitGenerator(name=split, gen_kwargs={"filepaths": downloaded_files}) |
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) |
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return split_generators |
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def _generate_examples(self, filepaths): |
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"""This function returns the examples in the raw (text) form by iterating on all the files.""" |
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id_ = 0 |
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for filepath in filepaths: |
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logger.info("Generating examples from = %s", filepath) |
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try: |
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with xz.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: |
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for line in f: |
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if line: |
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example = json.loads(line) |
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if example is not None and isinstance(example, dict): |
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timestamp = example.get("timestamp", "") |
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if isinstance(timestamp, str) and timestamp.endswith("Z"): |
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timestamp = timestamp[:-1] |
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yield id_, { |
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"url": example.get("url", ""), |
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"timestamp": timestamp, |
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"matches": example.get("matches", []), |
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"text": example.get("text", ""), |
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} |
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id_ += 1 |
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except Exception: |
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logger.exception("Error while processing file %s", filepath) |
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