Upload palito.py with huggingface_hub

palito.py

@@ -0,0 +1,160 @@
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+
+from seacrowd.utils import schemas
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import (DEFAULT_SEACROWD_VIEW_NAME,
+                                      DEFAULT_SOURCE_VIEW_NAME, Licenses,
+                                      Tasks)
+
+_DATASETNAME = "palito"
+_SOURCE_VIEW_NAME = DEFAULT_SOURCE_VIEW_NAME
+_UNIFIED_VIEW_NAME = DEFAULT_SEACROWD_VIEW_NAME
+
+_CITATION = """
+@inproceedings{dita-etal-2009-building,
+    title = "Building Online Corpora of {P}hilippine Languages",
+    author = "Dita, Shirley N.  and
+      Roxas, Rachel Edita O.  and
+      Inventado, Paul",
+    editor = "Kwong, Olivia",
+    booktitle = "Proceedings of the 23rd Pacific Asia Conference on Language, Information and Computation, Volume 2",
+    month = dec,
+    year = "2009",
+    address = "Hong Kong",
+    publisher = "City University of Hong Kong",
+    url = "https://aclanthology.org/Y09-2024",
+    pages = "646--653",
+}
+"""
+
+# We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_LANGUAGES = ["bik", "ceb", "hil", "ilo", "tgl", "pam", "pag", "war"]
+_LANG_CONFIG = {
+    "bik": "Bikol",
+    "ceb": "Cebuano",
+    "hil": "Hiligaynon",
+    "ilo": "Ilocano",
+    "tgl": "Tagalog",
+    "pam": "Kapampangan",
+    "pag": "Pangasinense",
+    "war": "Waray",
+}
+
+_LOCAL = False
+
+_DESCRIPTION = """\
+This paper aims at describing the building of the online corpora on Philippine
+languages as part of the online repository system called Palito. There are five components
+of the corpora: the top four major Philippine languages which are Tagalog, Cebuano,
+Ilocano and Hiligaynon and the Filipino Sign Language (FSL). The four languages are
+composed of 250,000-word written texts each, whereas the FSL is composed of seven
+thousand signs in video format. Categories of the written texts include creative writing (such
+as novels and stories) and religious texts (such as the Bible). Automated tools are provided
+for language analysis such as word count, collocates, and others. This is part of a bigger
+corpora building project for Philippine languages that would consider text, speech and
+video forms, and the corresponding development of automated tools for language analysis
+of these various forms.
+"""
+
+_HOMEPAGE = "https://github.com/imperialite/Philippine-Languages-Online-Corpora/tree/master/PALITO%20Corpus"
+
+_LICENSE = Licenses.LGPL.value
+
+_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
+
+_SOURCE_VERSION = "1.0.0"
+
+_SEACROWD_VERSION = "2024.06.20"
+
+_URLS = {
+    "literary": "https://raw.githubusercontent.com/imperialite/Philippine-Languages-Online-Corpora/master/PALITO%20Corpus/Data/{lang}_Literary_Text.txt",
+    "religious": "https://raw.githubusercontent.com/imperialite/Philippine-Languages-Online-Corpora/master/PALITO%20Corpus/Data/{lang}_Religious_Text.txt",
+}
+
+
+class PalitoDataset(datasets.GeneratorBasedBuilder):
+    """Palito corpus"""
+
+    subsets = [f"{_DATASETNAME}_{lang}" for lang in _LANGUAGES]
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name="{sub}_source".format(sub=subset),
+            version=datasets.Version(_SOURCE_VERSION),
+            description="Palito {sub} source schema".format(sub=subset),
+            schema="source",
+            subset_id="{sub}".format(sub=subset),
+        )
+        for subset in subsets
+    ] + [
+        SEACrowdConfig(
+            name="{sub}_seacrowd_ssp".format(sub=subset),
+            version=datasets.Version(_SEACROWD_VERSION),
+            description="Palito {sub} SEACrowd schema".format(sub=subset),
+            schema="seacrowd_ssp",
+            subset_id="{sub}".format(sub=subset),
+        )
+        for subset in subsets
+    ]
+
+    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
+        else:
+            raise ValueError(f"Invalid config schema: {self.config.schema}")
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        lang = self.config.name.split("_")[1]
+        filepaths = [Path(dl_manager.download(_URLS["literary"].format(lang=_LANG_CONFIG[lang]))), Path(dl_manager.download(_URLS["religious"].format(lang=_LANG_CONFIG[lang])))]
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepaths": filepaths},
+            ),
+        ]
+
+    def _generate_examples(self, filepaths: list[Path]) -> Tuple[int, Dict]:
+        counter = 0
+        for path in filepaths:
+            with open(path, encoding="utf-8") as f:
+                for line in f.readlines():
+                    if line.strip() == "":
+                        continue
+
+                    if self.config.schema == "source":
+                        yield (
+                            counter,
+                            {
+                                "id": str(counter),
+                                "text": line.strip(),
+                            },
+                        )
+                    elif self.config.schema == "seacrowd_ssp":
+                        yield (
+                            counter,
+                            {
+                                "id": str(counter),
+                                "text": line.strip(),
+                            },
+                        )
+
+                    counter += 1