





import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

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


__lowercase  :   Dict						      =logging.get_logger(__name__)


__lowercase  :   Optional[Any]						      ={"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

__lowercase  :   Optional[Any]						      ={
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
}

__lowercase  :   Dict						      ={
    """allenai/longformer-base-4096""": 4096,
    """allenai/longformer-large-4096""": 4096,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4096,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4096,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4096,
}




@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def     a__ (					):






   '''simple docstring'''






   UpperCAmelCase_											=(
       list(range(ord("!"  )  ,    ord("~"  ) + 1  )  ) + list(range(ord("¡"  )  ,    ord("¬"  ) + 1  )  ) + list(range(ord("®"  )  ,    ord("ÿ"  ) + 1  )  )
   )
   UpperCAmelCase_											=bs[:]
   UpperCAmelCase_											=0
   for b in range(2**8  ):
      if b not in bs:
         bs.append(lowercase__  )
         cs.append(2**8 + n  )
         n += 1
   UpperCAmelCase_											=[chr(lowercase__  ) for n in cs]
   return dict(zip(lowercase__  ,    lowercase__  )  )




def     a__ (					lowercase__  ):






   '''simple docstring'''






   UpperCAmelCase_											=set()
   UpperCAmelCase_											=word[0]
   for char in word[1:]:
      pairs.add((prev_char, char)  )
      UpperCAmelCase_											=char
   return pairs





class      A       (	__lowercase						):
    _snake_case							     =VOCAB_FILES_NAMES
    _snake_case							     =PRETRAINED_VOCAB_FILES_MAP
    _snake_case							     =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _snake_case							     =['''input_ids''', '''attention_mask''']



    def __init__(	self:						int		,  _lowerCAmelCase:						Optional[int]		,  _lowerCAmelCase:						List[Any]		,  _lowerCAmelCase:						Optional[Any]="replace"		,  _lowerCAmelCase:						Union[str, Any]="<s>"		,  _lowerCAmelCase:						int="</s>"		,  _lowerCAmelCase:						int="</s>"		,  _lowerCAmelCase:						List[Any]="<s>"		,  _lowerCAmelCase:						Tuple="<unk>"		,  _lowerCAmelCase:						Tuple="<pad>"		,  _lowerCAmelCase:						Dict="<mask>"		,  _lowerCAmelCase:						Any=False		,  **_lowerCAmelCase:						Any		,  )						->    Dict:
       '''simple docstring'''

       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else bos_token
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else eos_token
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else sep_token
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else cls_token
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else unk_token
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else pad_token

       # Mask token behave like a normal word, i.e. include the space before it
       UpperCAmelCase_											=AddedToken(_lowerCAmelCase		,  lstrip=_lowerCAmelCase		,  rstrip=_lowerCAmelCase       ) if isinstance(_lowerCAmelCase		,  _lowerCAmelCase       ) else mask_token

       super().__init__(
           errors=_lowerCAmelCase		,  bos_token=_lowerCAmelCase		,  eos_token=_lowerCAmelCase		,  unk_token=_lowerCAmelCase		,  sep_token=_lowerCAmelCase		,  cls_token=_lowerCAmelCase		,  pad_token=_lowerCAmelCase		,  mask_token=_lowerCAmelCase		,  add_prefix_space=_lowerCAmelCase		,  **_lowerCAmelCase		,  )

       with open(_lowerCAmelCase		,  encoding="utf-8"       ) as vocab_handle:
          UpperCAmelCase_											=json.load(_lowerCAmelCase       )
       UpperCAmelCase_											={v: k for k, v in self.encoder.items()}
       UpperCAmelCase_											=errors  # how to handle errors in decoding
       UpperCAmelCase_											=bytes_to_unicode()
       UpperCAmelCase_											={v: k for k, v in self.byte_encoder.items()}
       with open(_lowerCAmelCase		,  encoding="utf-8"       ) as merges_handle:
          UpperCAmelCase_											=merges_handle.read().split("\n"       )[1:-1]
       UpperCAmelCase_											=[tuple(merge.split()       ) for merge in bpe_merges]
       UpperCAmelCase_											=dict(zip(_lowerCAmelCase		,  range(len(_lowerCAmelCase       )       )       )       )
       UpperCAmelCase_											={}
       UpperCAmelCase_											=add_prefix_space

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       UpperCAmelCase_											=re.compile(r"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"       )



    @property
    def 	lowerCAmelCase__    (	self:						Tuple       )						->    Tuple:
       '''simple docstring'''

       return len(self.encoder       )



    def 	lowerCAmelCase__    (	self:						str       )						->    Union[str, Any]:
       '''simple docstring'''

       return dict(self.encoder		,  **self.added_tokens_encoder       )



    def 	lowerCAmelCase__    (	self:						List[str]		,  _lowerCAmelCase:						List[str]       )						->    str:
       '''simple docstring'''

       if token in self.cache:
          return self.cache[token]
       UpperCAmelCase_											=tuple(_lowerCAmelCase       )
       UpperCAmelCase_											=get_pairs(_lowerCAmelCase       )

       if not pairs:
          return token

       while True:
          UpperCAmelCase_											=min(_lowerCAmelCase		,  key=lambda _lowerCAmelCase       : self.bpe_ranks.get(_lowerCAmelCase		,  float("inf"       )       )       )
          if bigram not in self.bpe_ranks:
             break
          UpperCAmelCase_						,       UpperCAmelCase_											=bigram
          UpperCAmelCase_											=[]
          UpperCAmelCase_											=0
          while i < len(_lowerCAmelCase       ):
             try:
                UpperCAmelCase_											=word.index(_lowerCAmelCase		,  _lowerCAmelCase       )
             except ValueError:
                new_word.extend(word[i:]       )
                break
             else:
                new_word.extend(word[i:j]       )
                UpperCAmelCase_											=j

             if word[i] == first and i < len(_lowerCAmelCase       ) - 1 and word[i + 1] == second:
                new_word.append(first + second       )
                i += 2
             else:
                new_word.append(word[i]       )
                i += 1
          UpperCAmelCase_											=tuple(_lowerCAmelCase       )
          UpperCAmelCase_											=new_word
          if len(_lowerCAmelCase       ) == 1:
             break
          else:
             UpperCAmelCase_											=get_pairs(_lowerCAmelCase       )
       UpperCAmelCase_											=" ".join(_lowerCAmelCase       )
       UpperCAmelCase_											=word
       return word



    def 	lowerCAmelCase__    (	self:						Dict		,  _lowerCAmelCase:						Optional[Any]       )						->    Any:
       '''simple docstring'''

       UpperCAmelCase_											=[]
       for token in re.findall(self.pat		,  _lowerCAmelCase       ):
          UpperCAmelCase_											="".join(
              self.byte_encoder[b] for b in token.encode("utf-8"       )       )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
          bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_lowerCAmelCase       ).split(" "       )       )
       return bpe_tokens



    def 	lowerCAmelCase__    (	self:						Union[str, Any]		,  _lowerCAmelCase:						Union[str, Any]       )						->    str:
       '''simple docstring'''

       return self.encoder.get(_lowerCAmelCase		,  self.encoder.get(self.unk_token       )       )



    def 	lowerCAmelCase__    (	self:						Optional[int]		,  _lowerCAmelCase:						Any       )						->    Optional[Any]:
       '''simple docstring'''

       return self.decoder.get(_lowerCAmelCase       )



    def 	lowerCAmelCase__    (	self:						Tuple		,  _lowerCAmelCase:						Dict       )						->    str:
       '''simple docstring'''

       UpperCAmelCase_											="".join(_lowerCAmelCase       )
       UpperCAmelCase_											=bytearray([self.byte_decoder[c] for c in text]       ).decode("utf-8"		,  errors=self.errors       )
       return text



    def 	lowerCAmelCase__    (	self:						Union[str, Any]		,  _lowerCAmelCase:						str		,  _lowerCAmelCase:						Optional[str] = None       )						->    Tuple[str]:
       '''simple docstring'''

       if not os.path.isdir(_lowerCAmelCase       ):
          logger.error(F'Vocabulary path ({save_directory}) should be a directory'       )
          return
       UpperCAmelCase_											=os.path.join(
           _lowerCAmelCase		,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]       )
       UpperCAmelCase_											=os.path.join(
           _lowerCAmelCase		,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]       )

       with open(_lowerCAmelCase		,  "w"		,  encoding="utf-8"       ) as f:
          f.write(json.dumps(self.encoder		,  indent=2		,  sort_keys=_lowerCAmelCase		,  ensure_ascii=_lowerCAmelCase       ) + "\n"       )

       UpperCAmelCase_											=0
       with open(_lowerCAmelCase		,  "w"		,  encoding="utf-8"       ) as writer:
          writer.write("#version: 0.2\n"       )
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,  key=lambda _lowerCAmelCase       : kv[1]       ):
             if index != token_index:
                logger.warning(
                    F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                    " Please check that the tokenizer is not corrupted!"       )
                UpperCAmelCase_											=token_index
             writer.write(" ".join(_lowerCAmelCase       ) + "\n"       )
             index += 1

       return vocab_file, merge_file



    def 	lowerCAmelCase__    (	self:						Optional[int]		,  _lowerCAmelCase:						List[int]		,  _lowerCAmelCase:						Optional[List[int]] = None       )						->    List[int]:
       '''simple docstring'''

       if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
       UpperCAmelCase_											=[self.cls_token_id]
       UpperCAmelCase_											=[self.sep_token_id]
       return cls + token_ids_a + sep + sep + token_ids_a + sep



    def 	lowerCAmelCase__    (	self:						Union[str, Any]		,  _lowerCAmelCase:						List[int]		,  _lowerCAmelCase:						Optional[List[int]] = None		,  _lowerCAmelCase:						bool = False       )						->    List[int]:
       '''simple docstring'''

       if already_has_special_tokens:
          return super().get_special_tokens_mask(
              token_ids_a=_lowerCAmelCase		,  token_ids_a=_lowerCAmelCase		,  already_has_special_tokens=_lowerCAmelCase       )

       if token_ids_a is None:
          return [1] + ([0] * len(_lowerCAmelCase       )) + [1]
       return [1] + ([0] * len(_lowerCAmelCase       )) + [1, 1] + ([0] * len(_lowerCAmelCase       )) + [1]



    def 	lowerCAmelCase__    (	self:						Union[str, Any]		,  _lowerCAmelCase:						List[int]		,  _lowerCAmelCase:						Optional[List[int]] = None       )						->    List[int]:
       '''simple docstring'''

       UpperCAmelCase_											=[self.sep_token_id]
       UpperCAmelCase_											=[self.cls_token_id]

       if token_ids_a is None:
          return len(cls + token_ids_a + sep       ) * [0]
       return len(cls + token_ids_a + sep + sep + token_ids_a + sep       ) * [0]






    def 	lowerCAmelCase__    (	self:						int		,  _lowerCAmelCase:						List[str]		,  _lowerCAmelCase:						List[str]=False		,  **_lowerCAmelCase:						Dict       )						->    int:
       '''simple docstring'''

       UpperCAmelCase_											=kwargs.pop("add_prefix_space"		,  self.add_prefix_space       )
       if (is_split_into_words or add_prefix_space) and (len(_lowerCAmelCase       ) > 0 and not text[0].isspace()):
          UpperCAmelCase_											=" " + text
       return (text, kwargs)











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

import datasets


__lowercase  :   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}
}
"""


__lowercase  :   List[Any]						      ="""\
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.
"""


__lowercase  :   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      A       (	datasets.Metric						):



      def 	lowerCAmelCase__    (	self:						Any       )						->    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 	lowerCAmelCase__    (	self:						Any		,  _lowerCAmelCase:						Tuple		,  _lowerCAmelCase:						Union[str, Any]       )						->    Dict:
         '''simple docstring'''

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




