Upload pii_ner.py

pii_ner.py

@@ -0,0 +1,66 @@
+import json
+from itertools import chain
+import datasets
+
+logger = datasets.logging.get_logger(__name__)
+_DESCRIPTION = """[PII NER]"""
+_NAME = "pii_ner"
+_VERSION = "1.0.1"
+
+_URL = f'https://huggingface.co/datasets/acram/{_NAME}/raw/main/dataset'
+_URLS = {
+    str(datasets.Split.TEST): [f'{_URL}/test.json'],
+    str(datasets.Split.TRAIN): [f'{_URL}/train.json'],
+    str(datasets.Split.VALIDATION): [f'{_URL}/valid.json'],
+}
+
+
+class PiiNERConfig(datasets.BuilderConfig):
+    """BuilderConfig"""
+
+    def __init__(self, **kwargs):
+        """BuilderConfig.
+
+        Args:
+          **kwargs: keyword arguments forwarded to super.
+        """
+        super(PiiNERConfig, self).__init__(**kwargs)
+
+
+class PiiNER(datasets.GeneratorBasedBuilder):
+    """Dataset."""
+
+    BUILDER_CONFIGS = [
+        PiiNERConfig(name=_NAME, version=datasets.Version(_VERSION), description=_DESCRIPTION),
+    ]
+
+    def _split_generators(self, dl_manager):
+        downloaded_file = dl_manager.download_and_extract(_URLS)
+        return [datasets.SplitGenerator(name=i, gen_kwargs={"filepaths": downloaded_file[str(i)]})
+                for i in [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]]
+
+    def _generate_examples(self, filepaths):
+        _key = 0
+        for filepath in filepaths:
+            logger.info(f"generating examples from = {filepath}")
+            with open(filepath, encoding="utf-8") as f:
+                _list = [i for i in f.read().split('\n') if len(i) > 0]
+                for i in _list:
+                    data = json.loads(i)
+                    yield _key, data
+                    _key += 1
+
+    def _info(self):
+        #names = ["B-LOC", "B-MISC", "B-ORG", "B-PER", "I-LOC", "I-MISC", "I-ORG", "I-PER", "O"]
+        names=['O','B-NAME_STUDENT','I-NAME_STUDENT','B-STREET_ADDRESS','I-STREET_ADDRESS','B-USERNAME','B-EMAIL','B-URL_PERSONAL','B-PHONE_NUM','B-DRIVING_LICENSE',
+ 'B-PASSPORT','B-PAN_NUMBER','B-ID_NUM','B-AADHAR_ID']
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "tokens": datasets.Sequence(datasets.Value("string")),
+                    "tags": datasets.Sequence(datasets.features.ClassLabel(names=names)),
+                }
+            ),
+            supervised_keys=None,
+        )