Datasets:
Delete long-summarization-persian.py
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long-summarization-persian.py
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import csv
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import os
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import datasets
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_DESCRIPTION = """\
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This new dataset is designed to solve persian long summarization tasks.
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"""
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_URL = "./"
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class long_summarization_persianConfig(datasets.BuilderConfig):
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def __init__(self, **kwargs):
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"""BuilderConfig for long_summarization_persian.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(long_summarization_persianConfig, self).__init__(**kwargs)
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class long_summarization_persian(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIGS = [
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long_summarization_persianConfig(
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name="long_summarization_persian",
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version=datasets.Version("1.0.0"),
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description="long_summarization_persian dataset",
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),
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]
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"id": datasets.Value("string"),
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"article": datasets.Value("string"),
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"summary": datasets.Value("string")
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}
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),
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)
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def _split_generators(self, dl_manager):
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urls_to_download = {
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"train": f"{_URL}train.csv",
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"test": f"{_URL}test.csv",
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"validation": f"{_URL}validation.csv",
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}
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downloaded_files = dl_manager.download_and_extract(urls_to_download)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]}
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={"filepath": downloaded_files["validation"]},
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),
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]
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def _generate_examples(self, filepath):
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"""This function returns the examples in the raw (text) form."""
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with open(filepath, encoding="utf-8") as f:
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data = csv.DictReader(f)
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for id_, article in enumerate(data):
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article = article["article"]
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summary = article["summary"]
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yield id_, {
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"article": article,
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"summary": summary,
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}
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