| """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) | |
| } |