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udhr.py

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+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)}