Upload NER_Gujarati_data.py

NER_Gujarati_data.py

@@ -0,0 +1,92 @@
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+"""
+
+_DESCRIPTION = """\
+"""
+
+_URL = "https://huggingface.co/datasets/Red-8/NER_Gujarati_data/blob/main/datas.zip"
+
+class RedConfig(datasets.BuilderConfig):
+    """BuilderConfig for Red dataset"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig Red datset.
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(RedConfig, self).__init__(**kwargs)
+
+class Red(datasets.GeneratorBasedBuilder):
+
+    BUILDER_CONFIGS = [
+        RedConfig(
+            name="NER_Gujarati_data", version=datasets.Version("1.0.0")
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "ner_tags": datasets.Sequence(
+                        datasets.features.ClassLabel(
+                            names=[
+                                "O",
+                                "B-PERIOD",
+                                "I-PERIOD",
+                                "B-DURATION",
+                                "I-DURATION",
+                                "B-WEATHER",
+                                "I-WEATHER",
+                                "B-DIGIT",
+                                "I-DIGIT",
+                                "B-NUMINAL",
+                                "I-NUMINAL",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+
+        data_dir = dl_manager.download_and_extract(_URL)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir,"train_data.json"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir,"test_data.json"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir,"val_data.json"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, filepath):
+        """Yields examples as (key, example) tuples."""
+        with open(filepath,encoding="utf-8") as f:
+            for idx_, row in enumerate(f):
+                data = json.loads(row)
+                yield idx_, {"tokens": data["text"], "ner_tags": data["label"]}