EuclideaGame / EuclideaGame.py
Spyros Mouselinos
Markdown Updated
5a4be59
import pandas as pd
import datasets
from datasets import GeneratorBasedBuilder
_URL = './data/EuclideaGame.csv'
_CITATION = """\
@misc{mouselinos2024lines,
title={Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language Models},
author={Spyridon Mouselinos and Henryk Michalewski and Mateusz Malinowski},
year={2024},
eprint={2402.03877},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
"""
class EuclideaGame(GeneratorBasedBuilder):
def __init__(self, pack=None, **kwargs):
super().__init__(**kwargs)
self.pack = pack
def _info(self):
return datasets.DatasetInfo(
description="This dataset is a collection of the Euclidea "
"geometry game levels, alongside their provided solutions.",
features=datasets.Features({
"pack": datasets.ClassLabel(
names=["Alpha",
"Beta",
"Gamma",
"Delta",
"Epsilon",
"Zeta",
"Eta",
"Theta",
"Iota",
"Kappa",
"Lambda"]),
"level_id": datasets.Value("string"),
"question": datasets.Value("string"),
"solution_nl": datasets.Value("string"),
"solution_tool": datasets.Value("string"),
"solution_symbol": datasets.Value("string"),
"initial_symbol": datasets.Value("string")
}),
citation=_CITATION,
)
def _split_generators(self, dl_manager):
"""Point to local file path within the repository."""
data_path = dl_manager.download_and_extract(_URL)
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={"filepath": data_path, "pack": self.pack}
)
]
def _generate_examples(self, filepath, pack=None):
data = pd.read_csv(filepath)
if pack:
data = data[data['pack'].isin(pack)]
for idx, row in data.iterrows():
yield idx, {
'pack': row['pack'],
'level_id': row['level_id'],
'question': row['question'],
'solution_nl': row['solution_nl'],
'solution_tool': row['solution_tool'],
'solution_symbol': row['solution_symbol'],
'initial_symbol': row['initial_symbol']
}