"""mC4 dataset based on Common Crawl.""" import gzip import json import datasets logger = datasets.logging.get_logger(__name__) _VERSION = "0.0.2" _DESCRIPTION = """\ A colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "https://commoncrawl.org". This is the processed version of Google's mC4 dataset by AllenAI. """ _CITATION = """ @article{2019t5, author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu}, title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer}, journal = {arXiv e-prints}, year = {2019}, archivePrefix = {arXiv}, eprint = {1910.10683}, } """ _URL = "https://github.com/allenai/allennlp/discussions/5056" _DATA_URL = "https://huggingface.co/datasets/allenai/c4/resolve/1ddc917116b730e1859edef32896ec5c16be51d0/multilingual/c4-{language}{split_suffix}.tfrecord-{index:05d}-of-{n_shards:05d}.json.gz" _LANGUAGES = [ "af", "am", "ar", "az", "be", "bg", "bg-Latn", "bn", "ca", "ceb", "co", "cs", "cy", "da", "de", "el", "el-Latn", "en", "eo", "es", "et", "eu", "fa", "fi", "fil", "fr", "fy", "ga", "gd", "gl", "gu", "ha", "haw", "hi", "hi-Latn", "hmn", "ht", "hu", "hy", "id", "ig", "is", "it", "iw", "ja", "ja-Latn", "jv", "ka", "kk", "km", "kn", "ko", "ku", "ky", "la", "lb", "lo", "lt", "lv", "mg", "mi", "mk", "ml", "mn", "mr", "ms", "mt", "my", "ne", "nl", "no", "ny", "pa", "pl", "ps", "pt", "ro", "ru", "ru-Latn", "sd", "si", "sk", "sl", "sm", "sn", "so", "sq", "sr", "st", "su", "sv", "sw", "ta", "te", "tg", "th", "tr", "uk", "und", "ur", "uz", "vi", "xh", "yi", "yo", "zh", "zh-Latn", "zu", ] _N_SHARDS_PER_SPLIT = { 'af': {'validation': 1}, 'am': {'validation': 1}, 'ar': {'validation': 4}, 'az': {'validation': 1}, 'be': {'validation': 1}, 'bg': {'validation': 1}, 'bg-Latn': {'validation': 1}, 'bn': {'validation': 1}, 'ca': {'validation': 1}, 'ceb': {'validation': 1}, 'co': {'validation': 1}, 'cs': {'validation': 2}, 'cy': {'validation': 1}, 'da': {'validation': 1}, 'de': {'validation': 16}, 'el': {'validation': 2}, 'el-Latn': {'validation': 1}, 'en': {'validation': 128}, 'eo': {'validation': 1}, 'es': {'validation': 16}, 'et': {'validation': 1}, 'eu': {'validation': 1}, 'fa': {'validation': 2}, 'fi': {'validation': 1}, 'fil': {'validation': 1}, 'fr': {'validation': 16}, 'fy': {'validation': 1}, 'ga': {'validation': 1}, 'gd': {'validation': 1}, 'gl': {'validation': 1}, 'gu': {'validation': 1}, 'ha': {'validation': 1}, 'haw': {'validation': 1}, 'hi': {'validation': 2}, 'hi-Latn': {'validation': 1}, 'hmn': {'validation': 1}, 'ht': {'validation': 1}, 'hu': {'validation': 2}, 'hy': {'validation': 1}, 'id': {'validation': 4}, 'ig': {'validation': 1}, 'is': {'validation': 1}, 'it': {'validation': 8}, 'iw': {'validation': 1}, 'ja': {'validation': 8}, 'ja-Latn': {'validation': 1}, 'jv': {'validation': 1}, 'ka': {'validation': 1}, 'kk': {'validation': 1}, 'km': {'validation': 1}, 'kn': {'validation': 1}, 'ko': {'validation': 1}, 'ku': {'validation': 1}, 'ky': {'validation': 1}, 'la': {'validation': 1}, 'lb': {'validation': 1}, 'lo': {'validation': 1}, 'lt': {'validation': 1}, 'lv': {'validation': 1}, 'mg': {'validation': 1}, 'mi': {'validation': 1}, 'mk': {'validation': 1}, 'ml': {'validation': 1}, 'mn': {'validation': 1}, 'mr': {'validation': 1}, 'ms': {'validation': 1}, 'mt': {'validation': 1}, 'my': {'validation': 1}, 'ne': {'validation': 1}, 'nl': {'validation': 4}, 'no': {'validation': 1}, 'ny': {'validation': 1}, 'pa': {'validation': 1}, 'pl': {'validation': 4}, 'ps': {'validation': 1}, 'pt': {'validation': 4}, 'ro': {'validation': 2}, 'ru': {'validation': 32}, 'ru-Latn': {'validation': 1}, 'sd': {'validation': 1}, 'si': {'validation': 1}, 'sk': {'validation': 1}, 'sl': {'validation': 1}, 'sm': {'validation': 1}, 'sn': {'validation': 1}, 'so': {'validation': 1}, 'sq': {'validation': 1}, 'sr': {'validation': 1}, 'st': {'validation': 1}, 'su': {'validation': 1}, 'sv': {'validation': 2}, 'sw': {'validation': 1}, 'ta': {'validation': 1}, 'te': {'validation': 1}, 'tg': {'validation': 1}, 'th': {'validation': 1}, 'tr': {'validation': 4}, 'uk': {'validation': 2}, 'und': {'validation': 32}, 'ur': {'validation': 1}, 'uz': {'validation': 1}, 'vi': {'validation': 4}, 'xh': {'validation': 1}, 'yi': {'validation': 1}, 'yo': {'validation': 1}, 'zh': {'validation': 2}, 'zh-Latn': {'validation': 1}, 'zu': {'validation': 1} } class Mc4ValidationConfig(datasets.BuilderConfig): """BuilderConfig for mC4.""" def __init__(self, *args, languages, **kwargs): """BuilderConfig for mC4. Args: languages (:obj:`List[str]`): list of languages to load **kwargs: keyword arguments forwarded to super. """ super().__init__( *args, name="+".join(languages), **kwargs, ) self.languages = languages class Mc4Validation(datasets.GeneratorBasedBuilder): """mC4, a colossal, cleaned version of Common Crawl's web crawl corpus.""" BUILDER_CONFIGS = [Mc4ValidationConfig(languages=[lang], version=datasets.Version(_VERSION)) for lang in _LANGUAGES] BUILDER_CONFIG_CLASS = Mc4ValidationConfig def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features( { "text": datasets.Value("string"), "timestamp": datasets.Value("string"), "url": datasets.Value("string"), } ), supervised_keys=None, homepage=_URL, citation=_CITATION, ) def _split_generators(self, dl_manager): data_urls = {} for split in ["validation"]: data_urls[split] = [ _DATA_URL.format( language=lang, split_suffix="-validation" if split == "validation" else "", index=index, n_shards=_N_SHARDS_PER_SPLIT[lang][split], ) for lang in self.config.languages for index in range(_N_SHARDS_PER_SPLIT[lang][split]) ] validation_downloaded_files = dl_manager.download(data_urls["validation"]) return [ datasets.SplitGenerator( name=datasets.Split.VALIDATION, gen_kwargs={"filepaths": validation_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("generating examples from = %s", filepath) with gzip.open(open(filepath, "rb"), "rt", encoding="utf-8") as f: for line in f: if line: example = json.loads(line) yield id_, example id_ += 1