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License:
ART / art.py
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adds first dataloader
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import json
import os
import datasets
_CITATION = """\
@InProceedings{anli,
author = {Chandra, Bhagavatula and Ronan, Le Bras and Chaitanya, Malaviya and Keisuke, Sakaguchi and Ari, Holtzman
and Hannah, Rashkin and Doug, Downey and Scott, Wen-tau Yih and Yejin, Choi},
title = {Abductive Commonsense Reasoning},
year = {2020}
}"""
_DESCRIPTION = """\
the Abductive Natural Language Generation Dataset from AI2
"""
_DATA_URL = "https://storage.googleapis.com/ai2-mosaic/public/abductive-commonsense-reasoning-iclr2020/anlg.zip"
_HOMEPAGE = "https://github.com/allenai/abductive-commonsense-reasoning"
class ArtConfig(datasets.BuilderConfig):
"""BuilderConfig for Art."""
def __init__(self, **kwargs):
"""BuilderConfig for Art.
Args:
**kwargs: keyword arguments forwarded to super.
"""
super(ArtConfig, self).__init__(version=datasets.Version("0.1.0", ""), **kwargs)
class Art(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("0.1.0")
BUILDER_CONFIGS = [
ArtConfig(
name="anlg",
description="""\
Abductive Natural Language Generation Dataset from AI2.
""",
),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"gem_id": datasets.Value("string"),
"observation_1": datasets.Value("string"),
"observation_2": datasets.Value("string"),
"label": datasets.Value("string"),
}
),
homepage=_HOMEPAGE,
citation=_CITATION,
)
def _split_generators(self, dl_manager):
ds_splits = [datasets.Split.TRAIN, datasets.Split.VALIDATION, datasets.Split.TEST]
splits = ["train", "dev", "test"]
dl_dir = dl_manager.download_and_extract(_DATA_URL)
return [
datasets.SplitGenerator(
name=ds_split,
gen_kwargs={
"filepath": os.path.join(dl_dir, "anlg", f"{split}-w-comet-preds.jsonl"),
"split": split if split != "dev" else "validation" # adheres to GEM naming conventions
},
) for ds_split, split in zip(ds_splits, splits)
]
def _generate_examples(self, filepath, split):
with open(filepath, "r", encoding="utf-8") as f:
data = [json.loads(line) for line in f.readlines()]
for idx, row in enumerate(data):
label = row[f"hyp{row['label']}"]
yield idx, {
"gem_id": f"GEM-ART-{split}-{idx}",
"observation_1": row["obs1"],
"observation_2": row["obs2"],
"label": label,
}