Rename files to work as expected

Wikipedia-Horse-Dataset.py

@@ -0,0 +1,106 @@
+from __future__ import annotations
+
+import json
+import random
+from typing import Generator
+
+import datasets # type: ignore
+
+_CITATION = ""
+_DESCRIPTION = "This is a dataset of Wikipadia articles about Japan-trained horse manually labeled with the named entity label. I used DBpedia Japan searched Wikipedia Articles."
+_HOMEPAGE = "https://ja.dbpedia.org"
+_LICENSE = "This work is licensed under CC-BY-SA 3.0"
+_URL = "https://huggingface.co/datasets/DancingPrismPJ/Wikipedia-Horse-Dataset/raw/main/horse-dataset-600.json"
+
+class wikipediaHorseDatasetConfig(datasets.BuilderConfig):
+    def __init__(
+        self,
+        name: str = "default",
+        version: datasets.Version | str | None = datasets.Version("0.0.0"),
+        data_dir: str | None = None,
+        data_files: datasets.data_files.DataFilesDict | None = None,
+        description: str | None = _DESCRIPTION,
+        shuffle: bool = True,
+        seed: int = 42,
+        train_ratio: float = 0.8,
+        validation_ratio: float = 0.1,
+    ) -> None:
+        super().__init__(
+            name=name,
+            version=version,
+            data_dir=data_dir,
+            data_files=data_files,
+            description=description,
+        )
+        self.shuffle = shuffle
+        self.seed = seed
+        self.train_ratio = train_ratio
+        self.validation_ratio = validation_ratio
+
+class wikipediaHorseDataset(datasets.GeneratorBasedBuilder):
+    BUILDER_CONFIG_CLASS = wikipediaHorseDatasetConfig
+
+    def _info(self) -> datasets.DatasetInfo:
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "curid": datasets.Value("string"),
+                    "text": datasets.Value("string"),
+                    "entities": [
+                        {
+                            "name": datasets.Value("string"),
+                            "span": datasets.Sequence(
+                                datasets.Value("int64"), length=3
+                            ),
+                            "type": datasets.Value("string"),
+                        }
+                    ],
+                }
+            ),
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(
+        self, dl_manager: datasets.DownloadManager
+    ) -> list[datasets.SplitGenerator]:
+        dataset_dir = str(dl_manager.download_and_extract(_URL))
+        with open(dataset_dir, "r", encoding="utf-8") as f:
+            data = json.load(f)
+
+        if self.config.shuffle == True:
+            random.seed(self.config.seed)
+            random.shuffle(data)
+
+        num_data = len(data)
+        num_train_data = int(num_data * self.config.train_ratio)
+        num_validation_data = int(num_data * self.config.validation_ratio)
+        train_data = data[:num_train_data]
+        validation_data = data[num_train_data : num_train_data + num_validation_data]
+        test_data = data[num_train_data + num_validation_data :]
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"data": train_data},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"data": validation_data},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"data": test_data},
+            ),
+        ]
+
+    def _generate_examples(self, data: list[dict[str, str]]) -> Generator:
+        for key, d in enumerate(data):
+            yield key, {
+                "curid": d["curid"],
+                "text": d["text"],
+                "entities": d["entities"],
+            }
+
+