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"""TODO(hellaswag): Add a description here."""
import json
import datasets
# TODO(hellaswag): BibTeX citation
_CITATION = """\
@inproceedings{zellers2019hellaswag,
title={HellaSwag: Can a Machine Really Finish Your Sentence?},
author={Zellers, Rowan and Holtzman, Ari and Bisk, Yonatan and Farhadi, Ali and Choi, Yejin},
booktitle ={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
year={2019}
}
"""
_DESCRIPTION = """
HellaSwag: Can a Machine Really Finish Your Sentence? is a new dataset for commonsense NLI. A paper was published at ACL2019.
"""
_URL = "https://raw.githubusercontent.com/rowanz/hellaswag/master/data/"
_URLS = {
"train": _URL + "hellaswag_train.jsonl",
"test": _URL + "hellaswag_test.jsonl",
"dev": _URL + "hellaswag_val.jsonl",
}
class Hellaswag(datasets.GeneratorBasedBuilder):
"""TODO(hellaswag): Short description of my dataset."""
# TODO(hellaswag): Set up version.
VERSION = datasets.Version("0.1.0")
def _info(self):
# TODO(hellaswag): Specifies the datasets.DatasetInfo object
return datasets.DatasetInfo(
# This is the description that will appear on the datasets page.
description=_DESCRIPTION,
# datasets.features.FeatureConnectors
features=datasets.Features(
{
# These are the features of your dataset like images, labels ...
"ind": datasets.Value("int32"),
"activity_label": datasets.Value("string"),
"ctx_a": datasets.Value("string"),
"ctx_b": datasets.Value("string"),
"ctx": datasets.Value("string"),
"endings": datasets.features.Sequence(datasets.Value("string")),
"source_id": datasets.Value("string"),
"split": datasets.Value("string"),
"split_type": datasets.Value("string"),
"label": datasets.Value("string"),
}
),
# If there's a common (input, target) tuple from the features,
# specify them here. They'll be used if as_supervised=True in
# builder.as_dataset.
supervised_keys=None,
# Homepage of the dataset for documentation
homepage="https://rowanzellers.com/hellaswag/",
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
# TODO(hellaswag): Downloads the data and defines the splits
# dl_manager is a datasets.download.DownloadManager that can be used to
# download and extract URLs
urls_to_download = _URLS
dl_dir = dl_manager.download_and_extract(urls_to_download)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": dl_dir["train"]},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": dl_dir["test"]},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
# These kwargs will be passed to _generate_examples
gen_kwargs={"filepath": dl_dir["dev"]},
),
]
def _generate_examples(self, filepath):
"""Yields examples."""
# TODO(hellaswag): Yields (key, example) tuples from the dataset
with open(filepath, encoding="utf-8") as f:
for id_, row in enumerate(f):
data = json.loads(row)
yield id_, {
"ind": int(data["ind"]),
"activity_label": data["activity_label"],
"ctx_a": data.get("ctx_a", ""),
"ctx_b": data.get("ctx_b", ""),
"ctx": data["ctx"],
"endings": data.get("endings", []),
"source_id": data["source_id"],
"split": data["split"],
"split_type": data["split_type"],
"label": str(data.get("label", "")),
}
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