rottentomato01.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.
"""Rottento dataset."""


import json

import py7zr

import datasets


_CITATION = """
@article{gliwa2019samsum,
  title=rottento Corpus: Dataset for Abstractive Summarization},
  author={-},
  journal={-},
  year={2023}
}
"""

_DESCRIPTION = """
rottento Corpus contains annotated
summaries.
"""

_HOMEPAGE = "-"

_LICENSE = "-"

_URL = "https://huggingface.co/datasets/NavidVafaei/rottentomato01/tree/main/data/corpus.7z"


class Samsum(datasets.GeneratorBasedBuilder):
    """rottento Corpus dataset."""

    VERSION = datasets.Version("1.1.0")

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(name="Rottento"),
    ]

    def _info(self):
        features = datasets.Features(
            {                
                "movie": datasets.Value("string"),
                "reviews": datasets.Value("array"),
                "summary": datasets.Value("string"),
                "id": datasets.Value("string")
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            supervised_keys=None,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        path = dl_manager.download(_URL)
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={
                    "filepath": (path, "train.json"),
                    "split": "train",
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": (path, "test.json"),
                    "split": "test",
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION,
                gen_kwargs={
                    "filepath": (path, "val.json"),
                    "split": "val",
                },
            ),
        ]

    def _generate_examples(self, filepath, split):
        """Yields examples."""
        path, fname = filepath
        with open(path, "rb") as f:
            with py7zr.SevenZipFile(f, "r") as z:
                for name, bio in z.readall().items():
                    if name == fname:
                        data = json.load(bio)
        for example in data:
            yield example["id"], example