CC-NEWS-ES-titles.py

# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and 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.

# Lint as: python3
"""CC-NEWS-ES-titles: Title generation from CC-NEWS in Spanish."""


import json

import datasets
from datasets.tasks import Summarization


logger = datasets.logging.get_logger(__name__)


_CITATION = """ """
_DESCRIPTION = ""
_HOMEPAGE = ""

_LICENSE = ""

_URL = "https://huggingface.co/datasets/LeoCordoba/CC-NEWS-ES-titles/"
_URLS = {
    "train": _URL + "blob/main/train.json",
    "test": _URL + "blob/main/test.json",
    "eval": _URL + "blob/main/eval.json",
}

class CCNewsESTitlesConfig(datasets.BuilderConfig):
    """BuilderConfig for CCNewsESTitles."""

    def __init__(self, **kwargs):
        """BuilderConfig for CCNewsESTitles.
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(CCNewsESTitlesConfig, self).__init__(**kwargs)
        
class CCNewsESTitles(datasets.GeneratorBasedBuilder):
    """Title generation dataset in Spanish from CC-NEWS"""
    VERSION = datasets.Version("1.0.0")
    
    BUILDER_CONFIGS = [
        CCNewsESTitlesConfig(
        ),
    ]
    
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "output_test": datasets.Value("string")
                }
            ),
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )
    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        downloaded_files = dl_manager.download_and_extract(_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["eval"]}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"]})
        ]
    def _generate_examples(self, filepath):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", filepath)
        data = []
        with open(filepath, encoding="utf-8") as f:
            for line in f:
                data.append(json.loads(line))
        for obs in data:
            yield(obs)