
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A__   :		List[str] 		=logging.get_logger(__name__)

A__   :		int 		='▁'

A__   :		Tuple 		={'vocab_file': 'sentencepiece.bpe.model'}

A__   :		Optional[Any] 		={
    'vocab_file': {
        'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/sentencepiece.bpe.model',
    }
}

A__   :		Union[str, Any] 		={
    'facebook/xglm-564M': 2_048,
}







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =VOCAB_FILES_NAMES
 lowerCamelCase				       =PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase				       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCamelCase				       =['''input_ids''', '''attention_mask''']
 def __init__(   self			:    List[Any]				,   lowerCamelCase			:    int				,   lowerCamelCase			:    List[str]="<s>"				,   lowerCamelCase			:    Any="</s>"				,   lowerCamelCase			:    Optional[int]="</s>"				,   lowerCamelCase			:    int="<s>"				,   lowerCamelCase			:    Any="<unk>"				,   lowerCamelCase			:    Optional[int]="<pad>"				,   lowerCamelCase			:    Optional[Dict[str, Any]] = None				,   **lowerCamelCase			:    int				,   ):



   """simple docstring"""





   __A		:     Dict												=		{} if sp_model_kwargs is None else sp_model_kwargs

   # Compatibility with the original tokenizer
   __A		:     Optional[int]												=		7
   __A		:     List[Any]												=		[f"<madeupword{i}>" for i in range(self.num_madeup_words       )]

   __A		:     Union[str, Any]												=		kwargs.get("""additional_special_tokens"""				,   []       )
   kwargs["additional_special_tokens"] += [
       word for word in madeup_words if word not in kwargs["additional_special_tokens"]
   ]

   super().__init__(
       bos_token=lowerCamelCase				,   eos_token=lowerCamelCase				,   unk_token=lowerCamelCase				,   sep_token=lowerCamelCase				,   cls_token=lowerCamelCase				,   pad_token=lowerCamelCase				,   sp_model_kwargs=self.sp_model_kwargs				,   **lowerCamelCase				,   )

   __A		:     Any												=		spm.SentencePieceProcessor(**self.sp_model_kwargs       )
   self.sp_model.Load(str(lowerCamelCase       )       )
   __A		:     List[str]												=		vocab_file

   # Original fairseq vocab and spm vocab must be "aligned":
   # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
   # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
   # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
   # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

   # The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
   __A		:     Optional[Any]												=		1

   # Mimic fairseq token-to-id alignment for the first 4 token
   __A		:     List[str]												=		{"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

   __A		:     Any												=		len(self.sp_model       )
   __A		:     Dict												=		{f"<madeupword{i}>": sp_size + i + self.fairseq_offset for i in range(self.num_madeup_words       )}
   self.fairseq_tokens_to_ids.update(lowerCamelCase       )

   __A		:     str												=		{v: k for k, v in self.fairseq_tokens_to_ids.items()}
 def __getstate__(   self			:    Any       ):



   """simple docstring"""





   __A		:     Dict												=		self.__dict__.copy()
   __A		:     int												=		None
   __A		:     Dict												=		self.sp_model.serialized_model_proto()
   return state
 def __setstate__(   self			:    int				,   lowerCamelCase			:    List[Any]       ):



   """simple docstring"""





   __A		:     List[Any]												=		d

   # for backward compatibility
   if not hasattr(self				,   """sp_model_kwargs"""       ):
     __A		:     Optional[int]												=		{}

   __A		:     Dict												=		spm.SentencePieceProcessor(**self.sp_model_kwargs       )
   self.sp_model.LoadFromSerializedProto(self.sp_model_proto       )
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    List[int]				,   lowerCamelCase			:    Optional[List[int]] = None       ):



   """simple docstring"""





   if token_ids_a is None:
     return [self.sep_token_id] + token_ids_a
   __A		:     Optional[Any]												=		[self.sep_token_id]
   return sep + token_ids_a + sep + sep + token_ids_a
 def 		lowercase_(   self			:    Tuple				,   lowerCamelCase			:    List[int]				,   lowerCamelCase			:    Optional[List[int]] = None				,   lowerCamelCase			:    bool = False       ):



   """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       ))
   return [1] + ([0] * len(lowerCamelCase       )) + [1, 1] + ([0] * len(lowerCamelCase       ))
 def 		lowercase_(   self			:    Optional[Any]				,   lowerCamelCase			:    List[int]				,   lowerCamelCase			:    Optional[List[int]] = None       ):



   """simple docstring"""





   __A		:     str												=		[self.sep_token_id]

   if token_ids_a is None:
     return len(sep + token_ids_a       ) * [0]
   return len(sep + token_ids_a + sep + sep + token_ids_a       ) * [0]
 @property
 def 		lowercase_(   self			:    Any       ):



   """simple docstring"""





   return len(self.sp_model       ) + self.fairseq_offset + self.num_madeup_words
 def 		lowercase_(   self			:    Tuple       ):



   """simple docstring"""





   __A		:     str												=		{self.convert_ids_to_tokens(lowerCamelCase       ): i for i in range(self.vocab_size       )}
   vocab.update(self.added_tokens_encoder       )
   return vocab
 def 		lowercase_(   self			:    Union[str, Any]				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   return self.sp_model.encode(lowerCamelCase				,   out_type=lowerCamelCase       )
 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   if token in self.fairseq_tokens_to_ids:
     return self.fairseq_tokens_to_ids[token]
   __A		:     Optional[Any]												=		self.sp_model.PieceToId(lowerCamelCase       )

   # Need to return unknown token if the SP model returned 0
   return spm_id + self.fairseq_offset if spm_id else self.unk_token_id
 def 		lowercase_(   self			:    Any				,   lowerCamelCase			:    Any       ):



   """simple docstring"""





   if index in self.fairseq_ids_to_tokens:
     return self.fairseq_ids_to_tokens[index]
   return self.sp_model.IdToPiece(index - self.fairseq_offset       )
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    List[str]       ):



   """simple docstring"""





   __A		:     Dict												=		"""""".join(lowerCamelCase       ).replace(lowerCamelCase				,   """ """       ).strip()
   return out_string






 def 		lowercase_(   self			:    Tuple				,   lowerCamelCase			:    str				,   lowerCamelCase			:    Optional[str] = None       ):



   """simple docstring"""





   if not os.path.isdir(lowerCamelCase       ):
     logger.error(f"Vocabulary path ({save_directory}) should be a directory"       )
     return
   __A		:     int												=		os.path.join(
       lowerCamelCase				,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )

   if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowerCamelCase       ) and os.path.isfile(self.vocab_file       ):
     copyfile(self.vocab_file				,   lowerCamelCase       )
   elif not os.path.isfile(self.vocab_file       ):
     with open(lowerCamelCase				,   """wb"""       ) as fi:
       __A		:     List[str]												=		self.sp_model.serialized_model_proto()
       fi.write(lowerCamelCase       )

   return (out_vocab_file,)





'''simple docstring'''
def        A_     (						__SCREAMING_SNAKE_CASE						:  int			,     __SCREAMING_SNAKE_CASE						:  bool = False )				->       bool:





  """simple docstring"""

  if n == 2:
    return True
  if not n % 2 or n < 2:
    return False
  if n > 5 and n % 10 not in (1, 3, 7, 9):  # can quickly check last digit
    return False
  if n > 3_3170_4406_4679_8873_8596_1981 and not allow_probable:
    raise ValueError(
        """Warning: upper bound of deterministic test is exceeded. """
        """Pass allow_probable=True to allow probabilistic test. """
        """A return value of True indicates a probable prime.""" )
  # array bounds provided by analysis
  __A		:     Optional[int]												=		[
      2047,
      137_3653,
      2532_6001,
      32_1503_1751,
      2_1523_0289_8747,
      3_4747_4966_0383,
      341_5500_7172_8321,
      1,
      382_5123_0565_4641_3051,
      1,
      1,
      3186_6585_7834_0311_5116_7461,
      3_3170_4406_4679_8873_8596_1981,
  ]

  __A		:     Optional[int]												=		[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41]
  for idx, _p in enumerate(__SCREAMING_SNAKE_CASE			,     1 ):
    if n < _p:
      # then we have our last prime to check
      __A		:     Union[str, Any]												=		primes[:idx]
      break
  __A							,					__A		:     int												=		n - 1, 0
  # break up n -1 into a power of 2 (s) and
  # remaining odd component
  # essentially, solve for d * 2 ** s == n - 1
  while d % 2 == 0:
    d //= 2
    s += 1
  for prime in plist:
    __A		:     int												=		False
    for r in range(__SCREAMING_SNAKE_CASE ):
      __A		:     Optional[Any]												=		pow(__SCREAMING_SNAKE_CASE			,     d * 2**r			,     __SCREAMING_SNAKE_CASE )
      # see article for analysis explanation for m
      if (r == 0 and m == 1) or ((m + 1) % n == 0):
        __A		:     Optional[int]												=		True
        # this loop will not determine compositeness
        break
    if pr:
      continue
    # if pr is False, then the above loop never evaluated to true,
    # and the n MUST be composite
    return False
  return True







def        A_     (						)				->       None:





  """simple docstring"""

  assert not miller_rabin(561 )
  assert miller_rabin(563 )
  # 2047

  assert not miller_rabin(83_8201 )
  assert miller_rabin(83_8207 )
  # 1_373_653

  assert not miller_rabin(1731_6001 )
  assert miller_rabin(1731_6017 )
  # 25_326_001

  assert not miller_rabin(30_7838_6641 )
  assert miller_rabin(30_7838_6653 )
  # 3_215_031_751

  assert not miller_rabin(1_7130_4557_4801 )
  assert miller_rabin(1_7130_4557_4819 )
  # 2_152_302_898_747

  assert not miller_rabin(2_7797_9972_8307 )
  assert miller_rabin(2_7797_9972_8327 )
  # 3_474_749_660_383

  assert not miller_rabin(113_8500_2390_9441 )
  assert miller_rabin(113_8500_2390_9527 )
  # 341_550_071_728_321

  assert not miller_rabin(127_5041_0188_4880_4351 )
  assert miller_rabin(127_5041_0188_4880_4391 )
  # 3_825_123_056_546_413_051

  assert not miller_rabin(796_6646_4458_5077_8779_1867 )
  assert miller_rabin(796_6646_4458_5077_8779_1951 )
  # 318_665_857_834_031_151_167_461

  assert not miller_rabin(5528_4067_7446_6478_9766_0333 )
  assert miller_rabin(5528_4067_7446_6478_9766_0359 )
  # 3_317_044_064_679_887_385_961_981
  # upper limit for probabilistic test


if __name__ == "__main__":
     test_miller_rabin()



