utils/norwegian_parliament_backup.py

# coding=utf-8
# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
"""Norwegian Parliament Speeches (1998, 2016)"""
import csv

import datasets


_CITATION = """
@InProceedings{--,
  author = {---},
  title = {---},
  booktitle = {---},
  year = 2021,
  address = "---"
}
"""

_DESCRIPTION = """\
The Norwegian Parliament Speeches is a collection of text passages from
1998 to 2016 and pronounced at the Norwegian Parliament (Storting) by members
of the two major parties: Fremskrittspartiet and Sosialistisk Venstreparti.
"""


_HOMEPAGE = "https://github.com/NBAiLab/notram/"

_BASE_URL = "https://storage.googleapis.com/notram-public/finetune_datasets/parliament_speeches_1998_2016_frp_or_sv"
_URLS = {
    "train": f"{_BASE_URL}/train.csv",
    "dev": f"{_BASE_URL}/dev.csv",
    "test": f"{_BASE_URL}/test.csv",
}


class NorwegianParliament(datasets.GeneratorBasedBuilder):
    """Norwegian Parliament Speeches (1998, 2016)"""

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "label": datasets.ClassLabel(names=["Fremskrittspartiet", "Sosialistisk Venstreparti"]),
                    "date": datasets.Value("string"),
                }
            ),
            supervised_keys=None,
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        downloaded_files = dl_manager.download(_URLS)
        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):
        with open(filepath, encoding="utf-8") as csv_file:
            csv_reader = csv.reader(csv_file, delimiter=",")
            for idx, (label, text, _, date) in enumerate(csv_reader):
                label = int(label)
                yield int(idx), {
                    "text": text,
                    "label": label,
                    "date": date,
                }