add loader

NusaX-senti.py

@@ -0,0 +1,116 @@
+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+_LOCAL = False
+
+_LANGUAGES = ["ind", "ace", "ban", "bjn", "bbc", "bug", "jav", "mad", "min", "nij", "sun", "eng"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+
+_CITATION = """\
+@misc{winata2022nusax,
+      title={NusaX: Multilingual Parallel Sentiment Dataset for 10 Indonesian Local Languages},
+      author={Winata, Genta Indra and Aji, Alham Fikri and Cahyawijaya,
+      Samuel and Mahendra, Rahmad and Koto, Fajri and Romadhony,
+      Ade and Kurniawan, Kemal and Moeljadi, David and Prasojo,
+      Radityo Eko and Fung, Pascale and Baldwin, Timothy and Lau,
+      Jey Han and Sennrich, Rico and Ruder, Sebastian},
+      year={2022},
+      eprint={2205.15960},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+"""
+
+_DESCRIPTION = """\
+NusaX is a high-quality multilingual parallel corpus that covers 12 languages, Indonesian, English, and 10 Indonesian local languages, namely Acehnese, Balinese, Banjarese, Buginese, Madurese, Minangkabau, Javanese, Ngaju, Sundanese, and Toba Batak.
+NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English.
+"""
+
+_HOMEPAGE = "https://github.com/IndoNLP/nusax/tree/main/datasets/sentiment"
+
+_LICENSE = "Creative Commons Attribution Share-Alike 4.0 International"
+
+_SOURCE_VERSION = "1.0.0"
+
+_URLS = {
+    "train": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/train.csv",
+    "validation": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/valid.csv",
+    "test": "https://raw.githubusercontent.com/IndoNLP/nusax/main/datasets/sentiment/{lang}/test.csv",
+}
+
+LANGUAGES_MAP = {
+    "ace": "acehnese",
+    "ban": "balinese",
+    "bjn": "banjarese",
+    "bug": "buginese",
+    "eng": "english",
+    "ind": "indonesian",
+    "jav": "javanese",
+    "mad": "madurese",
+    "min": "minangkabau",
+    "nij": "ngaju",
+    "sun": "sundanese",
+    "bbc": "toba_batak",
+}
+
+
+class NusaXSenti(datasets.GeneratorBasedBuilder):
+    """NusaX-Senti is a 3-labels (positive, neutral, negative) sentiment analysis dataset for 10 Indonesian local languages + Indonesian and English."""
+
+    BUILDER_CONFIGS = [
+    datasets.BuilderConfig(
+        name = lang,
+        version = _SOURCE_VERSION,
+        description = f"NusaX-Senti: Sentiment analysis dataset for {lang}") 
+    for lang in LANGUAGES_MAP]
+
+    DEFAULT_CONFIG_NAME = "ind"
+
+    def _info(self) -> datasets.DatasetInfo:
+        features = datasets.Features(
+            {
+                "id": datasets.Value("string"),
+                "text": datasets.Value("string"),
+                "lang": datasets.Value("string"),
+                "label": datasets.Value("string"),
+            }
+        )
+
+        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."""
+        lang = self.config.name
+        train_csv_path = Path(dl_manager.download_and_extract(_URLS["train"].format(lang=LANGUAGES_MAP[lang])))
+        validation_csv_path = Path(dl_manager.download_and_extract(_URLS["validation"].format(lang=LANGUAGES_MAP[lang])))
+        test_csv_path = Path(dl_manager.download_and_extract(_URLS["test"].format(lang=LANGUAGES_MAP[lang])))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": train_csv_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"filepath": validation_csv_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": test_csv_path},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path) -> Tuple[int, Dict]:
+        df = pd.read_csv(filepath).reset_index()
+
+        for row in df.itertuples():
+            ex = {"id": str(row.id), "text": row.text, "label": row.label, "lang": self.config.name}
+            yield row.id, ex