'''simple docstring'''





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

import datasets


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


SCREAMING_SNAKE_CASE_:     Union[str, Any]  ='\\nThis metric is used to assess performance on the Mathematics Aptitude Test of Heuristics (MATH) dataset.\nIt first canonicalizes the inputs (e.g., converting "1/2" to "\\frac{1}{2}") and then computes accuracy.\n'


SCREAMING_SNAKE_CASE_:     List[Any]  =r'\nCalculates accuracy after canonicalizing inputs.\n\nArgs:\n    predictions: list of predictions to score. Each prediction\n        is a string that contains natural language and LaTex.\n    references: list of reference for each prediction. Each\n        reference is a string that contains natural language\n        and LaTex.\nReturns:\n    accuracy: accuracy after canonicalizing inputs\n        (e.g., converting "1/2" to "\\frac{1}{2}")\n\nExamples:\n    >>> metric = datasets.load_metric("competition_math")\n    >>> results = metric.compute(references=["\\frac{1}{2}"], predictions=["1/2"])\n    >>> print(results)\n    {\'accuracy\': 1.0}\n'




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



    def 					_lowercase						(self    :    Optional[Any] ):
         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 					_lowercase						(self    :    Tuple   ,			__a    :    Optional[int]   ,			__a    :    List[Any] ):
         UpperCAmelCase_           =   0.0
         for i, j in zip(__a   ,			__a ):
              n_correct += 1.0 if math_equivalence.is_equiv(__a   ,			__a ) else 0.0
         UpperCAmelCase_           =   n_correct / len(__a )
         return {
             "accuracy": accuracy,
         }





'''simple docstring'''





import warnings

from ...utils import logging
from .image_processing_clip import CLIPImageProcessor


SCREAMING_SNAKE_CASE_:     Union[str, Any]  =logging.get_logger(__name__)




class        __A      ( UpperCamelCase__	):



    def __init__(self    :    int   ,			*__a    :    Dict   ,			**__a    :    str ):
         warnings.warn(
             "The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"
             " use CLIPImageProcessor instead."   ,			__a   ,			)
         super().__init__(*__a   ,			**__a )




