






import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional, Tuple, Union, get_type_hints

import yaml


SCREAMING_SNAKE_CASE 							=						NewType('DataClass', Any)
SCREAMING_SNAKE_CASE 							=						NewType('DataClassType', Any)

def      _lowerCamelCase	(						__A    :							str )      ->					Optional[Any]:






    if isinstance(_lowercase		,		_lowercase ):
        return v
    if v.lower() in ("yes", "true", "t", "y", "1"):
        return True
    elif v.lower() in ("no", "false", "f", "n", "0"):
        return False
    else:
        raise ArgumentTypeError(
            f'''Truthy value expected: got {v} but expected one of yes/no, true/false, t/f, y/n, 1/0 (case insensitive).''' )

def      _lowerCamelCase	(						__A    :							list )      ->					Callable[[str], Any]:
    _UpperCAmelCase				:      Dict			  =				{str(_lowercase ): choice for choice in choices}
    return lambda __A : str_to_choice.get(_lowercase		,		_lowercase )

def      _lowerCamelCase	(						*,
    __A    :							Union[str, List[str]] = None		,		__A    :							str = None		,		__A    :							Any = dataclasses.MISSING		,		__A    :							Callable[[], Any] = dataclasses.MISSING		,		__A    :							dict = None		,		**__A    :							Union[str, Any]		,		)      ->					dataclasses.Field:






    if metadata is None:
        # Important, don't use as default param in function signature because dict is mutable and shared across function calls
        _UpperCAmelCase				:      Tuple			  =				{}
    if aliases is not None:
        _UpperCAmelCase				:      Union[str, Any]			  =				aliases
    if help is not None:
        _UpperCAmelCase				:      Optional[Any]			  =				help

    return dataclasses.field(metadata=_lowercase		,		default=_lowercase		,		default_factory=_lowercase		,		**_lowercase )


class 							A_    (						a__			):






 '''simple docstring'''




 _SCREAMING_SNAKE_CASE							:			Iterable[DataClassType]


 def __init__(	self							,  _A							,  **_A) ->		int:

     """simple docstring"""



     if "formatter_class" not in kwargs:
         _UpperCAmelCase				:      Any			  =				ArgumentDefaultsHelpFormatter
     super().__init__(**lowerCAmelCase__)
     if dataclasses.is_dataclass(lowerCAmelCase__):
         _UpperCAmelCase				:      Dict			  =				[dataclass_types]
     _UpperCAmelCase				:      List[str]			  =				list(lowerCAmelCase__)
     for dtype in self.dataclass_types:
         self._add_dataclass_arguments(lowerCAmelCase__)


 @staticmethod
 def  snake_case__				(	_A							,  _A) ->		Optional[int]:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				f'''--{field.name}'''
     _UpperCAmelCase				:      List[Any]			  =				field.metadata.copy()
     # field.metadata is not used at all by Data Classes,
     # it is provided as a third-party extension mechanism.
     if isinstance(field.type							,  lowerCAmelCase__):
         raise RuntimeError(
             '''Unresolved type detected, which should have been done with the help of '''
             '''`typing.get_type_hints` method by default''')

     _UpperCAmelCase				:      Dict			  =				kwargs.pop('''aliases'''							,  [])
     if isinstance(lowerCAmelCase__							,  lowerCAmelCase__):
         _UpperCAmelCase				:      Optional[Any]			  =				[aliases]

     _UpperCAmelCase				:      Union[str, Any]			  =				getattr(field.type							,  '''__origin__'''							,  field.type)
     if origin_type is Union or (hasattr(lowerCAmelCase__							,  '''UnionType''') and isinstance(lowerCAmelCase__							,  types.UnionType)):
         if str not in field.type.__args__ and (
             len(field.type.__args__) != 2 or type(lowerCAmelCase__) not in field.type.__args__
         ):
             raise ValueError(
                 '''Only `Union[X, NoneType]` (i.e., `Optional[X]`) is allowed for `Union` because'''
                 ''' the argument parser only supports one type per argument.'''
                 f''' Problem encountered in field \'{field.name}\'.''')
         if type(lowerCAmelCase__) not in field.type.__args__:
             # filter `str` in Union
             _UpperCAmelCase				:      List[Any]			  =				field.type.__args__[0] if field.type.__args__[1] == str else field.type.__args__[1]
             _UpperCAmelCase				:      str			  =				getattr(field.type							,  '''__origin__'''							,  field.type)
         elif bool not in field.type.__args__:
             # filter `NoneType` in Union (except for `Union[bool, NoneType]`)
             _UpperCAmelCase				:      str			  =				(
                 field.type.__args__[0] if isinstance(lowerCAmelCase__							,  field.type.__args__[1]) else field.type.__args__[1]
             )
             _UpperCAmelCase				:      Union[str, Any]			  =				getattr(field.type							,  '''__origin__'''							,  field.type)

        # A variable to store kwargs for a boolean field, if needed
        # so that we can init a `no_*` complement argument (see below)
     _UpperCAmelCase				:      List[Any]			  =				{}
     if origin_type is Literal or (isinstance(field.type							,  lowerCAmelCase__) and issubclass(field.type							,  lowerCAmelCase__)):
         if origin_type is Literal:
             _UpperCAmelCase				:      Union[str, Any]			  =				field.type.__args__
         else:
             _UpperCAmelCase				:      Optional[int]			  =				[x.value for x in field.type]

         _UpperCAmelCase				:      List[Any]			  =				make_choice_type_function(kwargs['''choices'''])

         if field.default is not dataclasses.MISSING:
             _UpperCAmelCase				:      Any			  =				field.default
         else:
             _UpperCAmelCase				:      Optional[int]			  =				True
     elif field.type is bool or field.type == Optional[bool]:
         # Copy the currect kwargs to use to instantiate a `no_*` complement argument below.
         # We do not initialize it here because the `no_*` alternative must be instantiated after the real argument
         _UpperCAmelCase				:      List[Any]			  =				copy(lowerCAmelCase__)

         # Hack because type=bool in argparse does not behave as we want.
         _UpperCAmelCase				:      Any			  =				string_to_bool
         if field.type is bool or (field.default is not None and field.default is not dataclasses.MISSING):
             # Default value is False if we have no default when of type bool.
             _UpperCAmelCase				:      int			  =				False if field.default is dataclasses.MISSING else field.default
             # This is the value that will get picked if we don't include --field_name in any way
             _UpperCAmelCase				:      List[Any]			  =				default
             # This tells argparse we accept 0 or 1 value after --field_name
             _UpperCAmelCase				:      str			  =				"?"
             # This is the value that will get picked if we do --field_name (without value)
             _UpperCAmelCase				:      Optional[Any]			  =				True
     elif isclass(lowerCAmelCase__) and issubclass(lowerCAmelCase__							,  lowerCAmelCase__):
         _UpperCAmelCase				:      int			  =				field.type.__args__[0]
         _UpperCAmelCase				:      str			  =				"+"
         if field.default_factory is not dataclasses.MISSING:
             _UpperCAmelCase				:      Tuple			  =				field.default_factory()
         elif field.default is dataclasses.MISSING:
             _UpperCAmelCase				:      List[str]			  =				True
     else:
         _UpperCAmelCase				:      str			  =				field.type
         if field.default is not dataclasses.MISSING:
             _UpperCAmelCase				:      Union[str, Any]			  =				field.default
         elif field.default_factory is not dataclasses.MISSING:
             _UpperCAmelCase				:      Optional[int]			  =				field.default_factory()
         else:
             _UpperCAmelCase				:      Tuple			  =				True
     parser.add_argument(lowerCAmelCase__							,  *lowerCAmelCase__							,  **lowerCAmelCase__)

     # Add a complement `no_*` argument for a boolean field AFTER the initial field has already been added.
     # Order is important for arguments with the same destination!
     # We use a copy of earlier kwargs because the original kwargs have changed a lot before reaching down
     # here and we do not need those changes/additional keys.
     if field.default is True and (field.type is bool or field.type == Optional[bool]):
         _UpperCAmelCase				:      Dict			  =				False
         parser.add_argument(f'''--no_{field.name}'''							,  action='''store_false'''							,  dest=field.name							,  **lowerCAmelCase__)


 def  snake_case__				(	self							,  _A) ->		List[str]:

     """simple docstring"""



     if hasattr(lowerCAmelCase__							,  '''_argument_group_name'''):
         _UpperCAmelCase				:      Any			  =				self.add_argument_group(dtype._argument_group_name)
     else:
         _UpperCAmelCase				:      Optional[Any]			  =				self

     try:
         _UpperCAmelCase				:      Dict[str, type]			  =				get_type_hints(lowerCAmelCase__)
     except NameError:
         raise RuntimeError(
             f'''Type resolution failed for {dtype}. Try declaring the class in global scope or '''
             '''removing line of `from __future__ import annotations` which opts in Postponed '''
             '''Evaluation of Annotations (PEP 563)''')
     except TypeError as ex:
         # Remove this block when we drop Python 3.9 support
         if sys.version_info[:2] < (3, 10) and "unsupported operand type(s) for |" in str(lowerCAmelCase__):
             _UpperCAmelCase				:      List[Any]			  =				".".join(map(lowerCAmelCase__							,  sys.version_info[:3]))
             raise RuntimeError(
                 f'''Type resolution failed for {dtype} on Python {python_version}. Try removing '''
                 '''line of `from __future__ import annotations` which opts in union types as '''
                 '''`X | Y` (PEP 604) via Postponed Evaluation of Annotations (PEP 563). To '''
                 '''support Python versions that lower than 3.10, you need to use '''
                 '''`typing.Union[X, Y]` instead of `X | Y` and `typing.Optional[X]` instead of '''
                 '''`X | None`.''') from ex
         raise

     for field in dataclasses.fields(lowerCAmelCase__):
         if not field.init:
             continue
         _UpperCAmelCase				:      Any			  =				type_hints[field.name]
         self._parse_dataclass_field(lowerCAmelCase__							,  lowerCAmelCase__)


 def  snake_case__				(	self							,  _A=None							,  _A=False							,  _A=True							,  _A=None							,  _A=None							,  ) ->		Tuple[DataClass, ...]:

     """simple docstring"""



     if args_file_flag or args_filename or (look_for_args_file and len(sys.argv)):
         _UpperCAmelCase				:      Dict			  =				[]

         if args_filename:
             args_files.append(Path(lowerCAmelCase__))
         elif look_for_args_file and len(sys.argv):
             args_files.append(Path(sys.argv[0]).with_suffix('''.args'''))

         # args files specified via command line flag should overwrite default args files so we add them last
         if args_file_flag:
             # Create special parser just to extract the args_file_flag values
             _UpperCAmelCase				:      int			  =				ArgumentParser()
             args_file_parser.add_argument(lowerCAmelCase__							,  type=lowerCAmelCase__							,  action='''append''')

             # Use only remaining args for further parsing (remove the args_file_flag)
             _UpperCAmelCase				:      Dict			  =				args_file_parser.parse_known_args(args=lowerCAmelCase__)
             _UpperCAmelCase				:      Optional[int]			  =				vars(lowerCAmelCase__).get(args_file_flag.lstrip('''-''')							,  lowerCAmelCase__)

             if cmd_args_file_paths:
                 args_files.extend([Path(lowerCAmelCase__) for p in cmd_args_file_paths])

         _UpperCAmelCase				:      Union[str, Any]			  =				[]
         for args_file in args_files:
             if args_file.exists():
                 file_args += args_file.read_text().split()

            # in case of duplicate arguments the last one has precedence
            # args specified via the command line should overwrite args from files, so we add them last
         _UpperCAmelCase				:      Any			  =				file_args + args if args is not None else file_args + sys.argv[1:]
     _UpperCAmelCase				:      List[str]			  =				self.parse_known_args(args=lowerCAmelCase__)
     _UpperCAmelCase				:      Dict			  =				[]
     for dtype in self.dataclass_types:
         _UpperCAmelCase				:      Any			  =				{f.name for f in dataclasses.fields(lowerCAmelCase__) if f.init}
         _UpperCAmelCase				:      Any			  =				{k: v for k, v in vars(lowerCAmelCase__).items() if k in keys}
         for k in keys:
             delattr(lowerCAmelCase__							,  lowerCAmelCase__)
         _UpperCAmelCase				:      Any			  =				dtype(**lowerCAmelCase__)
         outputs.append(lowerCAmelCase__)
     if len(namespace.__dict__) > 0:
         # additional namespace.
         outputs.append(lowerCAmelCase__)
     if return_remaining_strings:
         return (*outputs, remaining_args)
     else:
         if remaining_args:
             raise ValueError(f'''Some specified arguments are not used by the HfArgumentParser: {remaining_args}''')

         return (*outputs,)


 def  snake_case__				(	self							,  _A							,  _A = False) ->		Tuple[DataClass, ...]:

     """simple docstring"""



     _UpperCAmelCase				:      Union[str, Any]			  =				set(args.keys())
     _UpperCAmelCase				:      List[str]			  =				[]
     for dtype in self.dataclass_types:
         _UpperCAmelCase				:      int			  =				{f.name for f in dataclasses.fields(lowerCAmelCase__) if f.init}
         _UpperCAmelCase				:      Tuple			  =				{k: v for k, v in args.items() if k in keys}
         unused_keys.difference_update(inputs.keys())
         _UpperCAmelCase				:      List[str]			  =				dtype(**lowerCAmelCase__)
         outputs.append(lowerCAmelCase__)
     if not allow_extra_keys and unused_keys:
         raise ValueError(f'''Some keys are not used by the HfArgumentParser: {sorted(lowerCAmelCase__)}''')
     return tuple(lowerCAmelCase__)


 def  snake_case__				(	self							,  _A							,  _A = False) ->		Tuple[DataClass, ...]:

     """simple docstring"""



     with open(Path(lowerCAmelCase__)							,  encoding='''utf-8''') as open_json_file:
         _UpperCAmelCase				:      List[Any]			  =				json.loads(open_json_file.read())
     _UpperCAmelCase				:      Optional[Any]			  =				self.parse_dict(lowerCAmelCase__							,  allow_extra_keys=lowerCAmelCase__)
     return tuple(lowerCAmelCase__)


 def  snake_case__				(	self							,  _A							,  _A = False) ->		Tuple[DataClass, ...]:

     """simple docstring"""



     _UpperCAmelCase				:      int			  =				self.parse_dict(yaml.safe_load(Path(lowerCAmelCase__).read_text())							,  allow_extra_keys=lowerCAmelCase__)
     return tuple(lowerCAmelCase__)












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

import datasets


SCREAMING_SNAKE_CASE 							=						'\\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 							=						'\\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 							=						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			):






 '''simple docstring'''




 def  snake_case__				(	self) ->		Optional[Any]:

     """simple docstring"""



     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  snake_case__				(	self							,  _A							,  _A) ->		Tuple:

     """simple docstring"""



     _UpperCAmelCase				:      Tuple			  =				0.0
     for i, j in zip(_A							,  _A):
         n_correct += 1.0 if math_equivalence.is_equiv(_A							,  _A) else 0.0
     _UpperCAmelCase				:      Tuple			  =				n_correct / len(_A)
     return {
         "accuracy": accuracy,
     }




