Delete the script

ner-kazakh.py

@@ -1,158 +0,0 @@
-"""ner_kazakh"""
-
-import os
-import re
-
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """\
-"""
-
-_DESCRIPTION = "ner_kazakh"
-_URL = "./"
-_TRAINING_FILE = "ner_kazakh_train.txt"
-_DEV_FILE = "ner_kazakh_valid.txt"
-_TEST_FILE = "ner_kazakh_test.txt"
-
-class ner_kazakhConfig(datasets.BuilderConfig):
-	"""BuilderConfig for ner_kazakh"""
-
-	def __init__(self, **kwargs):
-		"""BuilderConfig for ner_kazakh.
-		Args:
-		  **kwargs: keyword arguments forwarded to super.
-		"""
-		super(ner_kazakhConfig, self).__init__(**kwargs)
-
-class ner_kazakh(datasets.GeneratorBasedBuilder):
-	"""ner_kazakh dataset."""
-
-	BUILDER_CONFIGS = [
-		ner_kazakhConfig(name = "ner_kazakh", version = datasets.Version("1.0.0"), description = "ner_kazakh"),
-	]
-
-	def _info(self):
-		return datasets.DatasetInfo(
-			description =_DESCRIPTION,
-			features = datasets.Features(
-				{
-					"index": datasets.Value("string"),
-					"sentence_id": datasets.Value("string"),
-					"tokens": datasets.Sequence(datasets.Value("string")),
-					"ner_tags": datasets.Sequence(
-						datasets.features.ClassLabel(
-							names = [
-								"O",
-								"B-ADAGE",
-								"I-ADAGE",
-								"B-ART",
-								"I-ART",
-								"B-CARDINAL",
-								"I-CARDINAL",
-								"B-CONTACT",
-								"I-CONTACT",
-								"B-DATE",
-								"I-DATE",
-								"B-DISEASE",
-								"I-DISEASE",
-								"B-EVENT",
-								"I-EVENT",
-								"B-FACILITY",
-								"I-FACILITY",
-								"B-GPE",
-								"I-GPE",
-								"B-LANGUAGE",
-								"I-LANGUAGE",
-								"B-LAW",
-								"I-LAW",
-								"B-LOCATION",
-								"I-LOCATION",
-								"B-MISCELLANEOUS",
-								"I-MISCELLANEOUS",
-								"B-MONEY",
-								"I-MONEY",
-								"B-NON_HUMAN",
-								"I-NON_HUMAN",
-								"B-NORP",
-								"I-NORP",
-								"B-ORDINAL",
-								"I-ORDINAL",
-								"B-ORGANISATION",
-								"I-ORGANISATION",
-								"B-PERSON",
-								"I-PERSON",
-								"B-PERCENTAGE",
-								"I-PERCENTAGE",
-								"B-POSITION",
-								"I-POSITION",
-								"B-PRODUCT",
-								"I-PRODUCT",
-								"B-PROJECT",
-								"I-PROJECT",
-								"B-QUANTITY",
-								"I-QUANTITY",
-								"B-TIME",
-								"I-TIME",
-							]
-						)
-					),
-				}
-			),
-			supervised_keys = None,
-			homepage = "",
-			citation = _CITATION,
-		)
-
-	def _split_generators(self, dl_manager):
-		"""Returns SplitGenerators."""
-		data_files = {
-			"train": f"{_URL}{_TRAINING_FILE}",
-			"dev": f"{_URL}{_DEV_FILE}",
-			"test": f"{_URL}{_TEST_FILE}",
-		}
-		downloaded_files = dl_manager.download_and_extract(data_files)
-
-		return [
-			datasets.SplitGenerator(name = datasets.Split.TRAIN, gen_kwargs = {"filepath": downloaded_files["train"]}),
-			datasets.SplitGenerator(name = datasets.Split.VALIDATION, gen_kwargs = {"filepath": downloaded_files["dev"]}),
-			datasets.SplitGenerator(name = datasets.Split.TEST, gen_kwargs = {"filepath": downloaded_files["test"]}),
-		]
-
-	def _generate_examples(self, filepath):
-		logger.info("⏳ Generating examples from = %s", filepath)
-		with open(filepath, encoding="utf-8") as f:
-			index = 0
-			sent_ids = []
-			tokens = []
-			ner_tags = []
-			for line in f:
-				if line.startswith("-DOCSTART-") or line == "" or line == "\n":
-					if tokens:
-						yield index, {
-							"index": str(index),
-							"sentence_id": sent_ids,
-							"tokens": tokens,
-							"ner_tags": ner_tags,
-						}
-						index += 1
-						sent_ids = []
-						tokens = []
-						ner_tags = []
-				else:
-					# ner_kazakh tokens are space separated
-					splits = line.split(" ")
-					if re.match(r"[A-Z]{3}\d{6}[A-Z]{3}", line):
-						sent_ids.append(splits[0])
-					else:
-						tokens.append(splits[0])
-						ner_tags.append(splits[1].rstrip())
-			# last example
-			if tokens:
-				yield index, {
-					"index": str(index),
-					"sentence_id": sent_ids,
-					"tokens": tokens,
-					"ner_tags": ner_tags,
-				}