File size: 9,675 Bytes
49197f8 581c47a 49197f8 581c47a 49197f8 f6a014c 49197f8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 |
"""mC4 dataset based on Common Crawl."""
import gzip
import json
import warnings
import datasets
logger = datasets.logging.get_logger(__name__)
_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": {"train": 64, "validation": 1},
"am": {"train": 16, "validation": 1},
"ar": {"train": 1024, "validation": 4},
"az": {"train": 256, "validation": 1},
"be": {"train": 128, "validation": 1},
"bg": {"train": 1024, "validation": 1},
"bg-Latn": {"train": 4, "validation": 1},
"bn": {"train": 512, "validation": 1},
"ca": {"train": 512, "validation": 1},
"ceb": {"train": 8, "validation": 1},
"co": {"train": 8, "validation": 1},
"cs": {"train": 1024, "validation": 2},
"cy": {"train": 256, "validation": 1},
"da": {"train": 1024, "validation": 1},
"de": {"train": 2048, "validation": 16},
"el": {"train": 1024, "validation": 2},
"el-Latn": {"train": 16, "validation": 1},
"en": {"train": 11264, "validation": 128},
"eo": {"train": 32, "validation": 1},
"es": {"train": 2048, "validation": 16},
"et": {"train": 256, "validation": 1},
"eu": {"train": 64, "validation": 1},
"fa": {"train": 1024, "validation": 2},
"fi": {"train": 1024, "validation": 1},
"fil": {"train": 64, "validation": 1},
"fr": {"train": 2048, "validation": 16},
"fy": {"train": 16, "validation": 1},
"ga": {"train": 16, "validation": 1},
"gd": {"train": 16, "validation": 1},
"gl": {"train": 128, "validation": 1},
"gu": {"train": 64, "validation": 1},
"ha": {"train": 8, "validation": 1},
"haw": {"train": 2, "validation": 1},
"hi": {"train": 1024, "validation": 2},
"hi-Latn": {"train": 16, "validation": 1},
"hmn": {"train": 8, "validation": 1},
"ht": {"train": 8, "validation": 1},
"hu": {"train": 1024, "validation": 2},
"hy": {"train": 128, "validation": 1},
"id": {"train": 1024, "validation": 4},
"ig": {"train": 4, "validation": 1},
"is": {"train": 128, "validation": 1},
"it": {"train": 1024, "validation": 8},
"iw": {"train": 1024, "validation": 1},
"ja": {"train": 1024, "validation": 8},
"ja-Latn": {"train": 8, "validation": 1},
"jv": {"train": 8, "validation": 1},
"ka": {"train": 256, "validation": 1},
"kk": {"train": 256, "validation": 1},
"km": {"train": 64, "validation": 1},
"kn": {"train": 64, "validation": 1},
"ko": {"train": 1024, "validation": 1},
"ku": {"train": 16, "validation": 1},
"ky": {"train": 64, "validation": 1},
"la": {"train": 64, "validation": 1},
"lb": {"train": 32, "validation": 1},
"lo": {"train": 8, "validation": 1},
"lt": {"train": 512, "validation": 1},
"lv": {"train": 256, "validation": 1},
"mg": {"train": 8, "validation": 1},
"mi": {"train": 4, "validation": 1},
"mk": {"train": 128, "validation": 1},
"ml": {"train": 128, "validation": 1},
"mn": {"train": 128, "validation": 1},
"mr": {"train": 1024, "validation": 1},
"ms": {"train": 512, "validation": 1},
"mt": {"train": 128, "validation": 1},
"my": {"train": 64, "validation": 1},
"ne": {"train": 256, "validation": 1},
"nl": {"train": 1024, "validation": 4},
"no": {"train": 1024, "validation": 1},
"ny": {"train": 4, "validation": 1},
"pa": {"train": 32, "validation": 1},
"pl": {"train": 1024, "validation": 4},
"ps": {"train": 16, "validation": 1},
"pt": {"train": 1024, "validation": 4},
"ro": {"train": 1024, "validation": 2},
"ru": {"train": 4096, "validation": 32},
"ru-Latn": {"train": 32, "validation": 1},
"sd": {"train": 64, "validation": 1},
"si": {"train": 64, "validation": 1},
"sk": {"train": 512, "validation": 1},
"sl": {"train": 256, "validation": 1},
"sm": {"train": 4, "validation": 1},
"sn": {"train": 8, "validation": 1},
"so": {"train": 64, "validation": 1},
"sq": {"train": 128, "validation": 1},
"sr": {"train": 256, "validation": 1},
"st": {"train": 2, "validation": 1},
"su": {"train": 4, "validation": 1},
"sv": {"train": 1024, "validation": 2},
"sw": {"train": 32, "validation": 1},
"ta": {"train": 256, "validation": 1},
"te": {"train": 128, "validation": 1},
"tg": {"train": 64, "validation": 1},
"th": {"train": 1024, "validation": 1},
"tr": {"train": 1024, "validation": 4},
"uk": {"train": 1024, "validation": 2},
"und": {"train": 3072, "validation": 32},
"ur": {"train": 128, "validation": 1},
"uz": {"train": 32, "validation": 1},
"vi": {"train": 1024, "validation": 4},
"xh": {"train": 2, "validation": 1},
"yi": {"train": 16, "validation": 1},
"yo": {"train": 2, "validation": 1},
"zh": {"train": 1024, "validation": 2},
"zh-Latn": {"train": 8, "validation": 1},
"zu": {"train": 8, "validation": 1},
}
class Mc4Config(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 Mc4(datasets.GeneratorBasedBuilder):
"""mC4, a colossal, cleaned version of Common Crawl's web crawl corpus."""
BUILDER_CONFIGS = [Mc4Config(languages=[lang]) for lang in _LANGUAGES]
BUILDER_CONFIG_CLASS = Mc4Config
def _info(self):
warnings.warn(
"Dataset 'mc4' is deprecated and will be deleted. Use 'allenai/c4' instead.",
FutureWarning,
)
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 ["train", "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])
]
train_downloaded_files = dl_manager.download(data_urls["train"])
validation_downloaded_files = dl_manager.download(data_urls["validation"])
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepaths": train_downloaded_files}),
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
|