Delete ORNL.py

ORNL.py

@@ -1,73 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace NLP Authors.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-# Lint as: python3
-"""Open Data Rechtspraak dutch topic classification dataset."""
-
-from __future__ import absolute_import, division, print_function
-
-import csv
-
-# import nlp # old loader
-import datasets
-from datasets.tasks import TextClassification
-
-
-_DESCRIPTION = """\
-still a WIP, Dataset originally comes from Open Data van de Rechtspraak"
-"""
-
-_TRAIN_DOWNLOAD_URL = "https://huggingface.co/datasets/Rodekool/ornl20/resolve/main/train.csv"
-_TEST_DOWNLOAD_URL  = "https://huggingface.co/datasets/Rodekool/ornl20/resolve/main/test.csv"
-
-
-class ORnl(datasets.GeneratorBasedBuilder):
-    """Open Data van de Rechtspraak dutch topic classification dataset."""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=['Ambtenarenrecht', 'Arbeidsrecht', 'Belastingrecht', 'Omgevingsrecht', 'Personen- en familierecht', 'Socialezekerheidsrecht', 'Verbintenissenrecht', 'Vreemdelingenrecht']),
-                }
-            ),
-            homepage="https://www.rechtspraak.nl/Uitspraken/paginas/open-data.aspx",
-        )
-
-    def _split_generators(self, dl_manager):
-        train_path = dl_manager.download_and_extract(_TRAIN_DOWNLOAD_URL)
-        test_path = dl_manager.download_and_extract(_TEST_DOWNLOAD_URL)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_path}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_path}),
-        ]
-
-    def _generate_examples(self, filepath):
-        """Generate Rechtspraak examples."""
-        with open(filepath, encoding="utf-8") as csv_file:
-            csv_reader = csv.reader(
-                csv_file, quotechar='"', delimiter=",", quoting=csv.QUOTE_ALL, skipinitialspace=True
-            )
-            for id_, row in enumerate(csv_reader):
-                label, title, description = row
-                
-                # Original labels are [1, 2, ... 25, 26] ->
-                # Re-map to [0, 1, ... 24, 25].
-                
-                label = int(label) - 1
-                text = " ".join((title, description))
-                yield id_, {"text": text, "label": label}