labels.py

# 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],
                }