Delete labels.py

labels.py

@@ -1,73 +0,0 @@
-# coding=utf-8
-# Copyright 2020 The HuggingFace Datasets 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.
-"""Yahoo! Answers Topic Classification Dataset"""
-
-
-_TRAIN_DOWNLOAD_URL = "https://drive.google.com/file/d/1Ehv1SSZ4n7ZLpUp7aSKNwHuC8UOgdfzL/view?usp=sharing"
-_TEST_DOWNLOAD_URL = "https://drive.google.com/file/d/1UWUuTEkK20Pz-H0rt78n91hHeVUhtCh1/view?usp=sharing"
-
-
-class AGNews(datasets.GeneratorBasedBuilder):
-    """AG News topic classification dataset."""
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "text": datasets.Value("string"),
-                    "label": datasets.features.ClassLabel(names=["World", "Sports", "Business", "Sci/Tech"]),
-                }
-            ),
-            homepage="http://groups.di.unipi.it/~gulli/AG_corpus_of_news_articles.html",
-            citation=_CITATION,
-            task_templates=[TextClassification(text_column="text", label_column="label")],
-        )
-
-    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 AG News 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, 3, 4] ->
-                #                   ['World', 'Sports', 'Business', 'Sci/Tech']
-                # Re-map to [0, 1, 2, 3].
-                label = int(label) - 1
-                text = " ".join((title, description))
-                yield id_, {"text": text, "label": label}
-
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            rows = csv.reader(f)
-            for i, row in enumerate(rows):
-                yield i, {
-                    "id": i,
-                    "topic": int(row[0]) - 1,
-                    "question_title": row[1],
-                    "question_content": row[2],
-                    "best_answer": row[3],
-                }