push updated test sets

.gitattributes

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naamapadam-pr.py

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+import json
+import os
+
+import datasets
+
+_CITATION = """\
+
+"""
+
+_DESCRIPTION = """\
+
+"""
+_HOMEPAGE = "https://indicnlp.ai4bharat.org/"
+
+_LICENSE = "Creative Commons Attribution-NonCommercial 4.0 International Public License"
+
+_URL = "https://huggingface.co/datasets/ai4bharat/naamapadam-pr/resolve/main/data/{}_IndicNER_v{}.zip"
+
+_LANGUAGES = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]
+
+
+class NaamapadamPR(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name="{}".format(lang), version=datasets.Version("1.0.0")
+        )
+        for lang in _LANGUAGES
+    ]
+
+    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-PER",
+                                "I-PER",
+                                "B-ORG",
+                                "I-ORG",
+                                "B-LOC",
+                                "I-LOC",
+                            ]
+                        )
+                    ),
+                }
+            ),
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            license=_LICENSE,
+            version=self.VERSION,
+        )
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        lang = str(self.config.name)
+        url = _URL.format(lang, self.VERSION.version_str[:-2])
+
+        data_dir = dl_manager.download_and_extract(url)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_train.json"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_test.json"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "filepath": os.path.join(data_dir, lang + "_val.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["words"], "ner_tags": data["ner"]}