"""The TempoSum benchmark.""" import json import os import datasets from contextlib import ExitStack _CITATION = """ @misc{cheang2023temposum, Author = {Chi Seng Cheang and Hou Pong Chan and Derek F. Wong and Xuebo Liu and Zhaocong Li and Yanming Sun and Shudong Liu and Lidia S. Chao}, Title = {TempoSum: Evaluating the Temporal Generalization of Abstractive Summarization}, Year = {2023}, } """ _DESCRIPTION = """TempoSum: Evaluating the Temporal Generalization of Abstractive Summarization""" _URL = "https://huggingface.co/datasets/chiseng-cheang/TempoSum/resolve/main/data/" _DOCUMENT = "document" _SUMMARY = "summary" _TITLE = "title" _DATASET_CONFIGS = { "BBC_in-distribution": { "urls": { datasets.Split.TEST: os.path.join(_URL, "bbc_in_distribution.tar.gz"), }, "available_features": [_DOCUMENT, _SUMMARY], }, "BBC_future": { "urls": { datasets.Split.TEST: os.path.join(_URL, "bbc_future.tar.gz"), }, "available_features": [_DOCUMENT, _SUMMARY], }, "CNN_in-distribution": { "urls": { datasets.Split.TEST: os.path.join(_URL, "cnn_in_distribution.tar.gz"), }, "available_features": [_DOCUMENT, _TITLE], }, "CNN_future": { "urls": { datasets.Split.TEST: os.path.join(_URL, "cnn_future.tar.gz"), }, "available_features": [_DOCUMENT, _TITLE], }, } class TempoSumConfig(datasets.BuilderConfig): """BuilderConfig for TempoSum.""" def __init__(self, urls, available_features, **kwargs): super(TempoSumConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs) self.features = datasets.Features({ feature: datasets.Value("string") for feature in available_features }) self.urls = urls self.available_features = available_features class TempoSum(datasets.GeneratorBasedBuilder): """The TempoSum benchmark.""" BUILDER_CONFIGS = [] for datasplit_name, datasplit_config in _DATASET_CONFIGS.items(): BUILDER_CONFIGS.append( TempoSumConfig( name=datasplit_name, urls=datasplit_config['urls'], available_features=datasplit_config['available_features'], ) ) def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, homepage="https://github.com/AndyCheang/TempoSum", ) def _split_generators(self, dl_manager): dl_dirs = dl_manager.download_and_extract(self.config.urls) splits = [] for split in dl_dirs: splits.append( datasets.SplitGenerator( name=split._name, gen_kwargs={ 'data_file': dl_dirs[split], 'split': split, } ) ) return splits def _generate_examples(self, data_file, split): features = self.config.available_features with ExitStack() as stack: files = [stack.enter_context(open(os.path.join(data_file, feature))) \ for feature in features] for idx, sample_data in enumerate(zip(*files)): yield idx, { feature: feature_data for (feature, feature_data) in zip(features, sample_data) }