




import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_albert import AlbertTokenizer
else:
      SCREAMING_SNAKE_CASE_						       =	None

SCREAMING_SNAKE_CASE_						       =	logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_						       =	{"""vocab_file""": """spiece.model""", """tokenizer_file""": """tokenizer.json"""}

SCREAMING_SNAKE_CASE_						       =	{
    """vocab_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/spiece.model""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/spiece.model""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/spiece.model""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/spiece.model""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/spiece.model""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/spiece.model""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/spiece.model""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/spiece.model""",
    },
    """tokenizer_file""": {
        """albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/tokenizer.json""",
        """albert-large-v1""": """https://huggingface.co/albert-large-v1/resolve/main/tokenizer.json""",
        """albert-xlarge-v1""": """https://huggingface.co/albert-xlarge-v1/resolve/main/tokenizer.json""",
        """albert-xxlarge-v1""": """https://huggingface.co/albert-xxlarge-v1/resolve/main/tokenizer.json""",
        """albert-base-v2""": """https://huggingface.co/albert-base-v2/resolve/main/tokenizer.json""",
        """albert-large-v2""": """https://huggingface.co/albert-large-v2/resolve/main/tokenizer.json""",
        """albert-xlarge-v2""": """https://huggingface.co/albert-xlarge-v2/resolve/main/tokenizer.json""",
        """albert-xxlarge-v2""": """https://huggingface.co/albert-xxlarge-v2/resolve/main/tokenizer.json""",
    },
}

SCREAMING_SNAKE_CASE_						       =	{
    """albert-base-v1""": 5_1_2,
    """albert-large-v1""": 5_1_2,
    """albert-xlarge-v1""": 5_1_2,
    """albert-xxlarge-v1""": 5_1_2,
    """albert-base-v2""": 5_1_2,
    """albert-large-v2""": 5_1_2,
    """albert-xlarge-v2""": 5_1_2,
    """albert-xxlarge-v2""": 5_1_2,
}

SCREAMING_SNAKE_CASE_						       =	"""▁"""

class 		UpperCamelCase__			(				__a       ):



     '''simple docstring'''

     __snake_case   :     List[str]		     =      VOCAB_FILES_NAMES
     __snake_case   :     Tuple		     =      PRETRAINED_VOCAB_FILES_MAP
     __snake_case   :     Optional[int]		     =      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __snake_case   :     int		     =      AlbertTokenizer






     def __init__(							self						:   List[str]						,lowerCamelCase__						:   List[Any]=None						,lowerCamelCase__						:   int=None						,lowerCamelCase__						:   Union[str, Any]=True						,lowerCamelCase__						:   Tuple=True						,lowerCamelCase__						:   Any=False						,lowerCamelCase__						:   Union[str, Any]="[CLS]"						,lowerCamelCase__						:   Any="[SEP]"						,lowerCamelCase__						:   Any="<unk>"						,lowerCamelCase__						:   str="[SEP]"						,lowerCamelCase__						:   int="<pad>"						,lowerCamelCase__						:   Optional[Any]="[CLS]"						,lowerCamelCase__						:   List[str]="[MASK]"						,**lowerCamelCase__						:   str						,)					->		Any:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						(
               AddedToken(UpperCamelCase__						,lstrip=UpperCamelCase__						,rstrip=UpperCamelCase__						,normalized=UpperCamelCase__	)
               if isinstance(UpperCamelCase__						,UpperCamelCase__	)
               else mask_token
           )

           super().__init__(
               UpperCamelCase__						,tokenizer_file=UpperCamelCase__						,do_lower_case=UpperCamelCase__						,remove_space=UpperCamelCase__						,keep_accents=UpperCamelCase__						,bos_token=UpperCamelCase__						,eos_token=UpperCamelCase__						,unk_token=UpperCamelCase__						,sep_token=UpperCamelCase__						,pad_token=UpperCamelCase__						,cls_token=UpperCamelCase__						,mask_token=UpperCamelCase__						,**UpperCamelCase__						,)

           SCREAMING_SNAKE_CASE		=						do_lower_case
           SCREAMING_SNAKE_CASE		=						remove_space
           SCREAMING_SNAKE_CASE		=						keep_accents
           SCREAMING_SNAKE_CASE		=						vocab_file
           SCREAMING_SNAKE_CASE		=						False if not self.vocab_file else True






     def     SCREAMING_SNAKE_CASE__  (							self						:   Optional[Any]						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None	)					->		List[int]:




           '''simple docstring'''


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






     def     SCREAMING_SNAKE_CASE__  (							self						:   Dict						,lowerCamelCase__						:   List[int]						,lowerCamelCase__						:   Optional[List[int]] = None	)					->		List[int]:




           '''simple docstring'''


           SCREAMING_SNAKE_CASE		=						[self.sep_token_id]
           SCREAMING_SNAKE_CASE		=						[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	) * [0] + len(token_ids_a + sep	) * [1]






     def     SCREAMING_SNAKE_CASE__  (							self						:   List[str]						,lowerCamelCase__						:   str						,lowerCamelCase__						:   Optional[str] = None	)					->		Tuple[str]:




           '''simple docstring'''


           if not self.can_save_slow_tokenizer:
                 raise ValueError(
                     """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
                     """tokenizer."""	)

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

           if os.path.abspath(self.vocab_file	) != os.path.abspath(UpperCamelCase__	):
                 copyfile(self.vocab_file						,UpperCamelCase__	)

           return (out_vocab_file,)









from __future__ import annotations



def        __lowercase       (				_SCREAMING_SNAKE_CASE     )			->       list[int]:


      '''simple docstring'''


      SCREAMING_SNAKE_CASE		=						2
      SCREAMING_SNAKE_CASE		=						[]
      while i * i <= n:
            if n % i:
                  i += 1
            else:
                  n //= i
                  factors.append(_SCREAMING_SNAKE_CASE     )
      if n > 1:
            factors.append(_SCREAMING_SNAKE_CASE     )
      return factors


if __name__ == "__main__":
      import doctest

      doctest.testmod()


