





"""simple docstring"""




import math_equivalence  # From: git+https://github.com/hendrycks/math.git

import datasets


a		:					Optional[int]	      =     '''\
@article{hendrycksmath2021,
  title={Measuring Mathematical Problem Solving With the MATH Dataset},
  author={Dan Hendrycks
    and Collin Burns
    and Saurav Kadavath
    and Akul Arora
    and Steven Basart
    and Eric Tang
    and Dawn Song
    and Jacob Steinhardt},
  journal={arXiv preprint arXiv:2103.03874},
  year={2021}
}
'''


a		:					int	      =     '''\
This metric is used to assess performance on the Mathematics Aptitude Test of Heuristics (MATH) dataset.
It first canonicalizes the inputs (e.g., converting "1/2" to "\\frac{1}{2}") and then computes accuracy.
'''


a		:					str	      =     r'''
Calculates accuracy after canonicalizing inputs.

Args:
    predictions: list of predictions to score. Each prediction
        is a string that contains natural language and LaTex.
    references: list of reference for each prediction. Each
        reference is a string that contains natural language
        and LaTex.
Returns:
    accuracy: accuracy after canonicalizing inputs
        (e.g., converting "1/2" to "\\frac{1}{2}")

Examples:
    >>> metric = datasets.load_metric("competition_math")
    >>> results = metric.compute(references=["\\frac{1}{2}"], predictions=["1/2"])
    >>> print(results)
    {\'accuracy\': 1.0}
'''


@datasets.utils.file_utils.add_end_docstrings(_DESCRIPTION						,			_KWARGS_DESCRIPTION		)
class 			__UpperCamelCase							(		datasets.Metric		):






							def        __a  (  self )      ->					Optional[int]:
								return datasets.MetricInfo(
								    description=_DESCRIPTION ,   citation=_CITATION ,   inputs_description=_KWARGS_DESCRIPTION ,   features=datasets.Features(
								        {
								            "predictions": datasets.Value("string" ),
								            "references": datasets.Value("string" ),
								        } ) ,   homepage="https://github.com/hendrycks/math" ,   codebase_urls=["https://github.com/hendrycks/math"] ,   )






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ )      ->					Optional[int]:
								a :						Any      =							0.0
								for i, j in zip(__snake_case ,   __snake_case ):
									n_correct += 1.0 if math_equivalence.is_equiv(__snake_case ,   __snake_case ) else 0.0
								a :						Any      =							n_correct / len(__snake_case )
								return {
								    "accuracy": accuracy,
								}









'''simple docstring'''






def   UpperCamelCase__ (						lowerCAmelCase				,      lowerCAmelCase    ):





      """simple docstring"""


      _lowerCAmelCase					=				""""""
      for word_or_phrase in separated:
            if not isinstance(lowerCAmelCase				,      lowerCAmelCase    ):
                  raise Exception("""join() accepts only strings to be joined"""    )
            joined += word_or_phrase + separator
      return joined.strip(lowerCAmelCase    )


if __name__ == "__main__":
      from doctest import testmod

      testmod()






