File size: 6,035 Bytes
c3efdac |
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 |
import os
from pathlib import Path
from typing import Dict, List, Tuple
import datasets
from pathlib import Path
from seacrowd.utils import schemas
from seacrowd.utils.configs import SEACrowdConfig
from seacrowd.utils.constants import Tasks, Licenses
_CITATION = """\
@misc{united1998universal,
title={The Universal Declaration of Human Rights, 1948-1998},
author={United Nations},
year={1998},
publisher={United Nations Dept. of Public Information New York}
}
"""
_DATASETNAME = "udhr"
_DESCRIPTION = """\
The Universal Declaration of Human Rights (UDHR) is a milestone document in the history of
human rights. Drafted by representatives with different legal and cultural backgrounds from
all regions of the world, it set out, for the first time, fundamental human rights to be
universally protected. The Declaration was adopted by the UN General Assembly in Paris on
10 December 1948 during its 183rd plenary meeting.
"""
_HOMEPAGE = "https://unicode.org/udhr/index.html"
_LICENSE = Licenses.UNKNOWN.value
_URLS = "https://unicode.org/udhr/assemblies/udhr_txt.zip"
_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
_SOURCE_VERSION = "1.0.0"
_SEACROWD_VERSION = "2024.06.20"
_LANGS = {
"ace": "Aceh",
"ban": "Bali",
"bcl": "Bicolano, Central",
"blt": "Tai Dam",
"bug": "Bugis",
"ceb": "Cebuano",
"cfm": "Chin, Falam", # flm
"cnh": "Chin, Haka",
"ctd": "Chin, Tedim",
"duu": "Drung",
"hil": "Hiligaynon",
"hlt": "Chin, Matu",
"hni": "Hani",
"hnj": "Hmong Njua", # blu
"ilo": "Ilocano",
"ind": "Indonesian",
"jav": "Javanese",
"jav_java": "Javanese (Javanese)",
"khm": "Khmer",
"kkh": "Khun",
"lao": "Lao",
"lus": "Mizo",
"mad": "Madura",
"min": "Minangkabau",
"mnw": "Mon",
"mya": "Burmese",
"pam": "Pampangan",
"shn": "Shan",
"sun": "Sunda",
"tdt": "Tetun Dili",
"tet": "Tetun",
"tgl": "Tagalog",
"tha": "Thai",
"vie": "Vietnamese",
"war": "Waray-waray",
"zlm": "Malay", # default mly_latn
}
_LOCAL=False
_LANGUAGES=["ace", "ban", "bcl", "blt", "bug", "ceb", "cfm", "cnh", "ctd", "duu", "hil", "hlt", "hni", "hnj", "ilo", "ind", "jav", "khm", "kkh", "lao", "lus", "mad", "min", "mnw", "mya", "pam", "shn", "sun", "tdt", "tet", "tgl", "tha", "vie", "war", "zlm"]
def seacrowd_config_constructor(src_lang, schema, version):
if src_lang == "":
raise ValueError(f"Invalid src_lang {src_lang}")
if schema not in ["source", "seacrowd_ssp"]:
raise ValueError(f"Invalid schema: {schema}")
return SEACrowdConfig(
name="udhr_{src}_{schema}".format(src=src_lang, schema=schema),
version=datasets.Version(version),
description="udhr {schema} schema for {src} language".format(schema=schema, src=_LANGS[src_lang]),
schema=schema,
subset_id="udhr_{src}".format(src=src_lang),
)
class UDHRDataset(datasets.GeneratorBasedBuilder):
"""
The Universal Declaration of Human Rights (UDHR) is a milestone document in the history of
human rights. Drafted by representatives with different legal and cultural backgrounds from
all regions of the world, it set out, for the first time, fundamental human rights to be
universally protected. The Declaration was adopted by the UN General Assembly in Paris on
10 December 1948 during its 183rd plenary meeting.
"""
SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
BUILDER_CONFIGS = [seacrowd_config_constructor(lang, "source", _SOURCE_VERSION) for lang in _LANGS] + [seacrowd_config_constructor(lang, "seacrowd_ssp", _SEACROWD_VERSION) for lang in _LANGS]
DEFAULT_CONFIG_NAME = "udhr_ind_source"
def _info(self) -> datasets.DatasetInfo:
if self.config.schema == "source":
features = datasets.Features(
{
"id": datasets.Value("string"),
"text": datasets.Value("string"),
}
)
elif self.config.schema == "seacrowd_ssp":
features = schemas.self_supervised_pretraining.features
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
)
def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
"""Returns SplitGenerators."""
urls = _URLS
data_dir = dl_manager.download_and_extract(urls)
lang = self.config.subset_id.split("_")
file_key=""
if lang[1] == "zlm":
file_key = "mly_latn"
elif lang[1] == "cfm":
file_key = "flm"
elif lang[1] == "hnj":
file_key = "blu"
elif lang[1] == "kkh":
file_key = "kkh_lana"
elif lang[1] == "duu":
file_key = "020"
elif lang[1] == "tdt":
file_key = "010"
elif len(lang)>2 and f"{lang[1]}_{lang[2]}" == "jav_java":
file_key = "jav_java"
else:
file_key = lang[1]
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"filepath": os.path.join(data_dir, f"udhr_{file_key}.txt".format(file_key=file_key)),
"split": "train",
},
),
]
def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
"""Yields examples as (key, example) tuples."""
data = []
with open(filepath, "r") as f:
data = [line.rstrip() for line in f.readlines()]
if self.config.schema == "source":
yield 0, {"id": Path(filepath).stem, "text": " ".join(data)}
elif self.config.schema == "seacrowd_ssp":
yield 0, {"id": Path(filepath).stem, "text": " ".join(data)}
|