


import os
from typing import List, Optional, Union

from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging


__lowerCAmelCase	: Any  				=logging.get_logger(__name__)

__lowerCAmelCase	: List[str]  				={'vocab_file': 'vocab.txt'}

__lowerCAmelCase	: Dict  				={
    'vocab_file': {
        'facebook/esm2_t6_8M_UR50D': 'https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt',
        'facebook/esm2_t12_35M_UR50D': 'https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt',
    },
}

__lowerCAmelCase	: int  				={
    'facebook/esm2_t6_8M_UR50D': 1_0_2_4,
    'facebook/esm2_t12_35M_UR50D': 1_0_2_4,
}


def        _UpperCamelCase							(      lowercase__      ):
						with open(lowercase__    ,       '''r'''      ) as f:
												__SCREAMING_SNAKE_CASE						:     Tuple					=		f.read().splitlines()
												return [l.strip() for l in lines]
class        _lowercase      (			A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			int						=		VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE__				:			str						=		PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE__				:			Dict						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE__				:			Dict						=		['''input_ids''', '''attention_mask''']


				def __init__(       self			:Dict			,			lowerCAmelCase__			:int			,			lowerCAmelCase__			:int="<unk>"			,			lowerCAmelCase__			:List[Any]="<cls>"			,			lowerCAmelCase__			:Optional[Any]="<pad>"			,			lowerCAmelCase__			:List[str]="<mask>"			,			lowerCAmelCase__			:List[Any]="<eos>"			,			**lowerCAmelCase__			:Optional[int]			,			)		->			Optional[int]:
										super().__init__(**lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     List[str]					=		load_vocab_file(lowerCAmelCase__	)
										__SCREAMING_SNAKE_CASE						:     Any					=		dict(enumerate(self.all_tokens	)	)
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		{tok: ind for ind, tok in enumerate(self.all_tokens	)}
										__SCREAMING_SNAKE_CASE						:     Tuple					=		unk_token
										__SCREAMING_SNAKE_CASE						:     Tuple					=		cls_token
										__SCREAMING_SNAKE_CASE						:     Dict					=		pad_token
										__SCREAMING_SNAKE_CASE						:     Dict					=		mask_token
										__SCREAMING_SNAKE_CASE						:     Union[str, Any]					=		eos_token
										__SCREAMING_SNAKE_CASE						:     Dict					=		self.all_tokens
										self._create_trie(self.unique_no_split_tokens	)


				def 		__magic_name__(       self			:str			,			lowerCAmelCase__			:int	)		->			str:
										return self._id_to_token.get(lowerCAmelCase__			,			self.unk_token	)


				def 		__magic_name__(       self			:List[str]			,			lowerCAmelCase__			:str	)		->			int:
										return self._token_to_id.get(lowerCAmelCase__			,			self._token_to_id.get(self.unk_token	)	)


				def 		__magic_name__(       self			:Tuple			,			lowerCAmelCase__			:List[str]			,			**lowerCAmelCase__			:Tuple	)		->			Tuple:
										return text.split()


				def 		__magic_name__(       self			:Union[str, Any]			,			lowerCAmelCase__			:Optional[int]=False	)		->			Optional[int]:
										return len(self._id_to_token	)


				def 		__magic_name__(       self			:Tuple	)		->			Any:
										return {token: i for i, token in enumerate(self.all_tokens	)}


				def 		__magic_name__(       self			:str			,			lowerCAmelCase__			:str	)		->			int:
										return self._token_to_id.get(lowerCAmelCase__			,			self._token_to_id.get(self.unk_token	)	)


				def 		__magic_name__(       self			:Optional[int]			,			lowerCAmelCase__			:int	)		->			str:
										return self._id_to_token.get(lowerCAmelCase__			,			self.unk_token	)


				def 		__magic_name__(       self			:Tuple			,			lowerCAmelCase__			:List[int]			,			lowerCAmelCase__			:Optional[List[int]] = None	)		->			List[int]:
										__SCREAMING_SNAKE_CASE						:     str					=		[self.cls_token_id]
										__SCREAMING_SNAKE_CASE						:     Optional[Any]					=		[self.eos_token_id]  # No sep token in ESM vocabulary
										if token_ids_a is None:
																if self.eos_token_id is None:
																						return cls + token_ids_a
																else:
																						return cls + token_ids_a + sep
										elif self.eos_token_id is None:
																raise ValueError('''Cannot tokenize multiple sequences when EOS token is not set!'''	)
										return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token


				def 		__magic_name__(       self			:Union[str, Any]			,			lowerCAmelCase__			:List			,			lowerCAmelCase__			:Optional[List] = None			,			lowerCAmelCase__			:bool = False	)		->			List[int]:
										if already_has_special_tokens:
																if token_ids_a is not None:
																						raise ValueError(
																						    '''You should not supply a second sequence if the provided sequence of '''
																						    '''ids is already formatted with special tokens for the model.'''	)

																return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
										__SCREAMING_SNAKE_CASE						:     Any					=		[1] + ([0] * len(lowerCAmelCase__	)) + [1]
										if token_ids_a is not None:
																mask += [0] * len(lowerCAmelCase__	) + [1]
										return mask


				def 		__magic_name__(       self			:Optional[Any]			,			lowerCAmelCase__			:List[str]			,			lowerCAmelCase__			:Union[str, Any]	)		->			Optional[int]:
										__SCREAMING_SNAKE_CASE						:     str					=		os.path.join(lowerCAmelCase__			,			(filename_prefix + '''-''' if filename_prefix else '''''') + '''vocab.txt'''	)
										with open(lowerCAmelCase__			,			'''w'''	) as f:
																f.write('''\n'''.join(self.all_tokens	)	)
										return (vocab_file,)


				@property
				def 		__magic_name__(       self			:int	)		->			int:
										return self.get_vocab_size(with_added_tokens=lowerCAmelCase__	)



				def 		__magic_name__(       self			:Optional[int]			,			lowerCAmelCase__			:Union[List[str], List[AddedToken]]			,			lowerCAmelCase__			:bool = False	)		->			int:
										return super()._add_tokens(lowerCAmelCase__			,			special_tokens=lowerCAmelCase__	)




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

import datasets


__lowerCAmelCase	: 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'


__lowerCAmelCase	: 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'


__lowerCAmelCase	: Optional[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        _lowercase      (			datasets.Metric       ):






				'''simple docstring'''



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