Delete pii_ner.py

pii_ner.py

@@ -1,66 +0,0 @@
-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,
-        )