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jadi_ide.py

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+from pathlib import Path
+from typing import Dict, List, Tuple
+
+import datasets
+import pandas as pd
+
+from nusacrowd.utils import schemas
+from nusacrowd.utils.configs import NusantaraConfig
+from nusacrowd.utils.constants import Tasks
+
+_CITATION = """\
+@article{hidayatullah2020attention,
+  title={Attention-based cnn-bilstm for dialect identification on javanese text},
+  author={Hidayatullah, Ahmad Fathan and Cahyaningtyas, Siwi and Pamungkas, Rheza Daffa},
+  journal={Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control},
+  pages={317--324},
+  year={2020}
+}
+"""
+
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_LOCAL = False
+
+_DATASETNAME = "jadi_ide"
+
+_DESCRIPTION = """\
+The JaDi-Ide dataset is a Twitter dataset for Javanese dialect identification, containing 16,498 
+data samples. The dialect is classified into `Standard Javanese`, `Ngapak Javanese`, and `East 
+Javanese` dialects.
+"""
+
+_HOMEPAGE = "https://github.com/fathanick/Javanese-Dialect-Identification-from-Twitter-Data"
+_LICENSE = "Unknown"
+_URLS = {
+    _DATASETNAME: "https://github.com/fathanick/Javanese-Dialect-Identification-from-Twitter-Data/raw/main/Update 16K_Dataset.xlsx",
+}
+# TODO check supported tasks
+_SUPPORTED_TASKS = [Tasks.EMOTION_CLASSIFICATION]
+_SOURCE_VERSION = "1.0.0"
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class JaDi_Ide(datasets.GeneratorBasedBuilder):
+    """The JaDi-Ide dataset is a Twitter dataset for Javanese dialect identification, containing 16,498 
+    data samples."""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="jadi_ide_source",
+            version=SOURCE_VERSION,
+            description="JaDi-Ide source schema",
+            schema="source",
+            subset_id="jadi_ide",
+        ),
+        NusantaraConfig(
+            name="jadi_ide_nusantara_text",
+            version=NUSANTARA_VERSION,
+            description="JaDi-Ide Nusantara schema",
+            schema="nusantara_text",
+            subset_id="jadi_ide",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "jadi_ide_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "id": datasets.Value("string"), 
+                    "text": datasets.Value("string"), 
+                    "label": datasets.Value("string")
+                }
+            )
+        elif self.config.schema == "nusantara_text":
+            features = schemas.text_features(["Jawa Timur", "Jawa Standar", "Jawa Ngapak"])
+   
+
+        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."""
+        # Dataset does not have predetermined split, putting all as TRAIN
+        urls = _URLS[_DATASETNAME]
+        base_dir = Path(dl_manager.download(urls))
+        data_files = {"train": base_dir}
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": data_files["train"],
+                    "split": "train",
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        df = pd.read_excel(filepath)
+        df.columns = ["id", "text", "label"]
+
+        if self.config.schema == "source":
+            for idx, row in enumerate(df.itertuples()):
+                ex = {
+                    "id": str(idx),
+                    "text": row.text,
+                    "label": row.label,
+                }
+                yield idx, ex
+
+        elif self.config.schema == "nusantara_text":
+            for idx, row in enumerate(df.itertuples()):
+                ex = {
+                    "id": str(idx),
+                    "text": row.text,
+                    "label": row.label,
+                }
+                yield idx, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")