mathqa.py 1.54 KB
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"""
MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms
https://arxiv.org/pdf/1905.13319.pdf

MathQA is a large-scale dataset of 37k English multiple-choice math word problems
covering multiple math domain categories by modeling operation programs corresponding
to word problems in the AQuA dataset (Ling et al., 2017).

Homepage: https://math-qa.github.io/math-QA/

@misc{amini2019mathqa,
      title={MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms}, 
      author={Aida Amini and Saadia Gabriel and Peter Lin and Rik Koncel-Kedziorski and Yejin Choi and Hannaneh Hajishirzi},
      year={2019},
      eprint={1905.13319},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
"""
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import re
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from lm_eval.base import MultipleChoiceTask
from . common import HFTask

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class MathQA(HFTask, MultipleChoiceTask):
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    VERSION = 0
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    DATASET_PATH = "math_qa"
    DATASET_NAME = None

    def has_training_docs(self):
        return True

    def has_validation_docs(self):
        return True

    def has_test_docs(self):
        return True

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    def _convert_standard(self, doc):
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        answer_idx = ['a', 'b', 'c', 'd', 'e'].index(doc['correct'])
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        choices = [c[4:].rstrip(" ,") for c in re.findall(r"[abcd] \) .*?, |e \) .*?$", doc['options'])]
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        out_doc = {
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            "query": "Question: " + doc['Problem'] +"\nAnswer:",
            "choices": choices,
            "gold": answer_idx,
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        }
        return out_doc
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    def doc_to_text(self, doc):
        return doc["query"]