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id_sts.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 = """
+"""
+
+_DATASETNAME = "id_sts"
+
+_DESCRIPTION = """\
+SemEval is a series of international natural language processing (NLP) research workshops whose mission is
+to advance the current state of the art in semantic analysis and to help create high-quality annotated datasets in a
+range of increasingly challenging problems in natural language semantics. This is a translated version of SemEval Dataset
+from 2012-2016 for Semantic Textual Similarity Task to Indonesian language.
+"""
+
+_HOMEPAGE = "https://github.com/ahmadizzan/sts-indo"
+
+_LANGUAGES = ["ind"]  # We follow ISO639-3 language code (https://iso639-3.sil.org/code_tables/639/data)
+_LOCAL = False
+
+_LICENSE = "Unknown"
+
+_URLS = {
+    _DATASETNAME: {
+        "train": "https://raw.githubusercontent.com/ahmadizzan/sts-indo/master/data/final-data/train.tsv",
+        "test": "https://raw.githubusercontent.com/ahmadizzan/sts-indo/master/data/final-data/test.tsv",
+    }
+}
+
+_SUPPORTED_TASKS = [Tasks.SEMANTIC_SIMILARITY]
+
+_SOURCE_VERSION = "1.0.0"
+
+_NUSANTARA_VERSION = "1.0.0"
+
+
+class IdSts(datasets.GeneratorBasedBuilder):
+    """id_sts, translated version of SemEval Dataset
+    from 2012-2016 for Semantic Textual Similarity Task to Indonesian language"""
+
+    SOURCE_VERSION = datasets.Version(_SOURCE_VERSION)
+    NUSANTARA_VERSION = datasets.Version(_NUSANTARA_VERSION)
+
+    BUILDER_CONFIGS = [
+        NusantaraConfig(
+            name="id_sts_source",
+            version=SOURCE_VERSION,
+            description="ID_STS source schema",
+            schema="source",
+            subset_id="id_sts",
+        ),
+        NusantaraConfig(
+            name="id_sts_nusantara_pairs_score",
+            version=NUSANTARA_VERSION,
+            description="ID_STS Nusantara schema",
+            schema="nusantara_pairs_score",
+            subset_id="id_sts",
+        ),
+    ]
+
+    DEFAULT_CONFIG_NAME = "id_sts_source"
+
+    def _info(self) -> datasets.DatasetInfo:
+
+        if self.config.schema == "source":
+            features = datasets.Features(
+                {
+                    "text_1": datasets.Value("string"),
+                    "text_2": datasets.Value("string"),
+                    "label": datasets.Value("float64"),
+                }
+            )
+        elif self.config.schema == "nusantara_pairs_score":
+            features = schemas.pairs_features_score()
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
+        urls = _URLS[_DATASETNAME]
+        train_data_path = Path(dl_manager.download(urls["train"]))
+        test_data_path = Path(dl_manager.download(urls["test"]))
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"filepath": train_data_path, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": test_data_path, "split": "test"},
+            ),
+        ]
+
+    def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]:
+        """Yields examples as (key, example) tuples."""
+        # Dataset does not have id, using row index as id
+        df = pd.read_csv(filepath, delimiter="\t").reset_index()
+        df.columns = ["id", "score", "original_text_1", "original_text_2", "source", "text_1", "text_2"]
+
+        if self.config.schema == "source":
+            for row in df.itertuples():
+                ex = {"text_1": row.text_1, "text_2": row.text_2, "label": row.score}
+                yield row.id, ex
+
+        elif self.config.schema == "nusantara_pairs_score":
+            for row in df.itertuples():
+                ex = {"id": str(row.id), "text_1": row.text_1, "text_2": row.text_2, "label": row.score}
+                yield row.id, ex
+        else:
+            raise ValueError(f"Invalid config: {self.config.name}")