# 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. | |
# TODO: Address all TODOs and remove all explanatory comments | |
"""TODO: Add a description here.""" | |
import json | |
import os | |
import datasets | |
# TODO: Add BibTeX citation | |
# Find for instance the citation on arxiv or on the dataset repo/website | |
_CITATION = """\ | |
@article{qin2024infobench, | |
title={InFoBench: Evaluating Instruction Following Ability in Large Language Models}, | |
author={Yiwei Qin and Kaiqiang Song and Yebowen Hu and Wenlin Yao and Sangwoo Cho and Xiaoyang Wang and Xuansheng Wu and Fei Liu and Pengfei Liu and Dong Yu}, | |
year={2024}, | |
eprint={2401.03601}, | |
archivePrefix={arXiv}, | |
primaryClass={cs.CL} | |
} | |
""" | |
# TODO: Add description of the dataset here | |
# You can copy an official description | |
_DESCRIPTION = """\ | |
InFoBench: Evaluating Instruction Following Ability in Large Language Models | |
""" | |
# TODO: Add a link to an official homepage for the dataset here | |
_HOMEPAGE = "" | |
# TODO: Add the licence for the dataset here if you can find it | |
_LICENSE = """MIT License | |
Copyright (c) 2023 qinyiwei | |
Permission is hereby granted, free of charge, to any person obtaining a copy | |
of this software and associated documentation files (the "Software"), to deal | |
in the Software without restriction, including without limitation the rights | |
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | |
copies of the Software, and to permit persons to whom the Software is | |
furnished to do so, subject to the following conditions: | |
The above copyright notice and this permission notice shall be included in all | |
copies or substantial portions of the Software. | |
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | |
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | |
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | |
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | |
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | |
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | |
SOFTWARE. | |
""" | |
# TODO: Add link to the official dataset URLs here | |
# The HuggingFace Datasets library doesn't host the datasets but only points to the original files. | |
# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method) | |
_URLS = { | |
"test": "https://huggingface.co/datasets/kqsong/InFoBench/raw/main/InfoBench.json", | |
} | |
# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case | |
class NewDataset(datasets.GeneratorBasedBuilder): | |
"""TODO: Short description of my dataset.""" | |
VERSION = datasets.Version("1.0.0") | |
# This is an example of a dataset with multiple configurations. | |
# If you don't want/need to define several sub-sets in your dataset, | |
# just remove the BUILDER_CONFIG_CLASS and the BUILDER_CONFIGS attributes. | |
# If you need to make complex sub-parts in the datasets with configurable options | |
# You can create your own builder configuration class to store attribute, inheriting from datasets.BuilderConfig | |
# BUILDER_CONFIG_CLASS = MyBuilderConfig | |
# You will be able to load one or the other configurations in the following list with | |
# data = datasets.load_dataset('my_dataset', 'first_domain') | |
# data = datasets.load_dataset('my_dataset', 'second_domain') | |
BUILDER_CONFIGS = [ | |
datasets.BuilderConfig(name="test", version=VERSION, description="Test Split") | |
] | |
DEFAULT_CONFIG_NAME = "first_domain" # It's not mandatory to have a default configuration. Just use one if it make sense. | |
def _info(self): | |
# TODO: This method specifies the datasets.DatasetInfo object which contains informations and typings for the dataset | |
features = datasets.Features( | |
{ | |
"id": datasets.Value(dtype="string", id=None), | |
"subset": datasets.Value(dtype="string", id=None), | |
"category": datasets.Value(dtype="string", id=None), | |
"input": datasets.Value(dtype="string", id=None), | |
"instruction": datasets.Value(dtype="string", id=None), | |
"decomposed_questions": datasets.Sequence(feature=datasets.Value(dtype="string", id=None), length=-1, id=None), | |
"question_label": datasets.Sequence(feature=datasets.Sequence(feature=datasets.Value(dtype="string", id=None), length=-1, id=None), length=-1, id=None), | |
} | |
) | |
return datasets.DatasetInfo( | |
# This is the description that will appear on the datasets page. | |
description=_DESCRIPTION, | |
# This defines the different columns of the dataset and their types | |
features=features, # Here we define them above because they are different between the two configurations | |
# If there's a common (input, target) tuple from the features, uncomment supervised_keys line below and | |
# specify them. They'll be used if as_supervised=True in builder.as_dataset. | |
# supervised_keys=("sentence", "label"), | |
# Homepage of the dataset for documentation | |
homepage=_HOMEPAGE, | |
# License for the dataset if available | |
license=_LICENSE, | |
# Citation for the dataset | |
citation=_CITATION, | |
) | |
def _split_generators(self, dl_manager): | |
# TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration | |
# If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name | |
# dl_manager is a datasets.download.DownloadManager that can be used to download and extract URLS | |
# It can accept any type or nested list/dict and will give back the same structure with the url replaced with path to local files. | |
# By default the archives will be extracted and a path to a cached folder where they are extracted is returned instead of the archive | |
urls = _URLS[self.config.name] | |
data_dir = dl_manager.download_and_extract(urls) | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
# These kwargs will be passed to _generate_examples | |
gen_kwargs={ | |
"filepath": os.path.join(data_dir, "test.jsonl"), | |
"split": "test" | |
}, | |
), | |
] | |
# method parameters are unpacked from `gen_kwargs` as given in `_split_generators` | |
def _generate_examples(self, filepath, split): | |
# TODO: This method handles input defined in _split_generators to yield (key, example) tuples from the dataset. | |
# The `key` is for legacy reasons (tfds) and is not important in itself, but must be unique for each example. | |
with open(filepath, encoding="utf-8") as f: | |
for key, row in enumerate(f): | |
data = json.loads(row) | |
yield key, data | |