Upload filipino_gay_lang.py with huggingface_hub

filipino_gay_lang.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from seacrowd.utils.configs import SEACrowdConfig
+from seacrowd.utils.constants import SCHEMA_TO_FEATURES, TASK_TO_SCHEMA, Tasks
+
+# TODO: Add BibTeX citation
+_CITATION = r"""\
+@article{oco2015witchebelles,
+  author    = {Oco, Nathaniel and Fajutagana, Raymart and Lim, Christine Mae and Mi{\~n}on, Judi Diane and Morano, Julie-Ann and Tinoco, Ryan Christian},
+  title     = {Witchebelles Anata Magcharot kay Mudra na Nagsusuba si Akech: Developing a Rule-based Unidirectional Beki Lingo to Filipino Translator},
+  journal   = {Journal of Sciences, Technology and Arts Research},
+  volume    = {1},
+  number    = {1},
+  year      = {2015}
+}
+"""
+
+_LOCAL = False
+_LANGUAGES = ["fil"]
+_DATASETNAME = "filipino_gay_lang"
+_DESCRIPTION = """\
+The dataset contains 4000+ Filipino tweets in gay language or lingo also called swardspeak in slang terminology.
+The tweet dataset was collected from February 2013 to November 2014 using the following commonly used gay words as filters: jinet ("hot"), ditey ("here"), imbyerna ("annoying"), etc.
+The original paper makes use of the corpus to develop a gay language translator to understand the meaning of phrases using gay words in Filipino.
+"""
+
+_HOMEPAGE = "https://github.com/imperialite/Philippine-Languages-Online-Corpora/tree/master/Tweets/Gay%20language"
+_LICENSE = "CC-BY-SA 4.0"
+_URLS = {
+    "gl_01": "https://github.com/imperialite/Philippine-Languages-Online-Corpora/raw/master/Tweets/Gay%20language/gl%20-%2001.xlsx",
+    "gl_02": "https://github.com/imperialite/Philippine-Languages-Online-Corpora/raw/master/Tweets/Gay%20language/gl%20-%2002.xlsx",
+    "gl_03": "https://github.com/imperialite/Philippine-Languages-Online-Corpora/raw/master/Tweets/Gay%20language/gl%20-%2003.xlsx",
+}
+
+_SUPPORTED_TASKS = [Tasks.SELF_SUPERVISED_PRETRAINING]
+_SOURCE_VERSION = "1.0.0"
+_SEACROWD_VERSION = "2024.06.20"
+
+
+class FilipinoGayLangDataset(datasets.GeneratorBasedBuilder):
+    """This dataset contains 4000+ Filipino tweets in gay lingo/Beki/Swardspeak."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION)
+
+    SEACROWD_SCHEMA_NAME = TASK_TO_SCHEMA[_SUPPORTED_TASKS[0]].lower()
+
+    BUILDER_CONFIGS = [
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_source",
+            version=SOURCE_VERSION,
+            description=f"{_DATASETNAME} source schema",
+            schema="source",
+            subset_id=f"{_DATASETNAME}",
+        ),
+        SEACrowdConfig(
+            name=f"{_DATASETNAME}_seacrowd_{SEACROWD_SCHEMA_NAME}",
+            version=SEACROWD_VERSION,
+            description=f"{_DATASETNAME} SEACrowd schema",
+            schema=f"seacrowd_{SEACROWD_SCHEMA_NAME}",
+            subset_id=f"{_DATASETNAME}",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = f"{_DATASETNAME}_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features({"index": datasets.Value("string"), "text": datasets.Value("string")})
+        elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
+            features = SCHEMA_TO_FEATURES[self.SEACROWD_SCHEMA_NAME.upper()]
+
+        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."""
+
+        data_files = {
+            "gl_01": Path(dl_manager.download(_URLS["gl_01"])),
+            "gl_02": Path(dl_manager.download(_URLS["gl_02"])),
+            "gl_03": Path(dl_manager.download(_URLS["gl_03"])),
+        }
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": [data_files["gl_01"], data_files["gl_02"], data_files["gl_03"]], "split": "train"},
+            )
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+
+        df = pd.concat((pd.read_excel(file) for file in filepath), ignore_index=True).reset_index()
+
+        if self.config.schema == "source":
+            for row in df.itertuples():
+                ex = {"index": str(row.index), "text": row.message}
+                yield row.index, ex
+        elif self.config.schema == f"seacrowd_{self.SEACROWD_SCHEMA_NAME}":
+            for row in df.itertuples():
+                ex = {"id": str(row.index), "text": row.message}
+                yield row.index, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")