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

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
 from .tokenization_deberta_va import DebertaVaTokenizer
else:
 UpperCAmelCase      		=					None

UpperCAmelCase      		=					logging.get_logger(__name__)

UpperCAmelCase      		=					{'''vocab_file''': '''spm.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase      		=					{
    '''vocab_file''': {
        '''microsoft/deberta-v2-xlarge''': '''https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xxlarge''': '''https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model''',
        '''microsoft/deberta-v2-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model'''
        ),
        '''microsoft/deberta-v2-xxlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model'''
        ),
    }
}

UpperCAmelCase      		=					{
    '''microsoft/deberta-v2-xlarge''': 5_12,
    '''microsoft/deberta-v2-xxlarge''': 5_12,
    '''microsoft/deberta-v2-xlarge-mnli''': 5_12,
    '''microsoft/deberta-v2-xxlarge-mnli''': 5_12,
}

UpperCAmelCase      		=					{
    '''microsoft/deberta-v2-xlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xlarge-mnli''': {'''do_lower_case''': False},
    '''microsoft/deberta-v2-xxlarge-mnli''': {'''do_lower_case''': False},
}




class  __lowerCAmelCase	(							a_    ):



 '''simple docstring'''
 _lowerCamelCase    :						Union[str, Any]					     =			VOCAB_FILES_NAMES
 _lowerCamelCase    :						Any					     =			PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase    :						Union[str, Any]					     =			PRETRAINED_INIT_CONFIGURATION
 _lowerCamelCase    :						Union[str, Any]					     =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase    :						Tuple					     =			DebertaVaTokenizer

 def __init__(      self							:		int							,      lowerCamelCase							:		Any=None							,      lowerCamelCase							:		List[Any]=None							,      lowerCamelCase							:		Optional[Any]=False							,      lowerCamelCase							:		List[Any]=False							,      lowerCamelCase							:		Tuple="[CLS]"							,      lowerCamelCase							:		Optional[Any]="[SEP]"							,      lowerCamelCase							:		Tuple="[UNK]"							,      lowerCamelCase							:		Dict="[SEP]"							,      lowerCamelCase							:		Union[str, Any]="[PAD]"							,      lowerCamelCase							:		List[Any]="[CLS]"							,      lowerCamelCase							:		Union[str, Any]="[MASK]"							,      **lowerCamelCase							:		Optional[Any]							,      )			->				None:
        super().__init__(
            lowerCamelCase							,      tokenizer_file=lowerCamelCase							,      do_lower_case=lowerCamelCase							,      bos_token=lowerCamelCase							,      eos_token=lowerCamelCase							,      unk_token=lowerCamelCase							,      sep_token=lowerCamelCase							,      pad_token=lowerCamelCase							,      cls_token=lowerCamelCase							,      mask_token=lowerCamelCase							,      split_by_punct=lowerCamelCase							,      **lowerCamelCase							,      )

        _UpperCamelCase  :							int	    =	do_lower_case
        _UpperCamelCase  :							Tuple	    =	split_by_punct
        _UpperCamelCase  :							List[str]	    =	vocab_file
        _UpperCamelCase  :							Dict	    =	False if not self.vocab_file else True

 def        __snake_case       (      self							:		List[Any]							,      lowerCamelCase							:		List[str]							,      lowerCamelCase							:		Optional[int]=None	)			->				Optional[Any]:

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

 def        __snake_case       (      self							:		Dict							,      lowerCamelCase							:		str							,      lowerCamelCase							:		Dict=None							,      lowerCamelCase							:		int=False	)			->				List[str]:

        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 not None:
               return [1] + ([0] * len(lowerCamelCase	)) + [1] + ([0] * len(lowerCamelCase	)) + [1]
        return [1] + ([0] * len(lowerCamelCase	)) + [1]

 def        __snake_case       (      self							:		Optional[Any]							,      lowerCamelCase							:		List[str]							,      lowerCamelCase							:		List[Any]=None	)			->				Any:
        _UpperCamelCase  :							Optional[int]	    =	[self.sep_token_id]
        _UpperCamelCase  :							List[str]	    =	[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        __snake_case       (      self							:		Any							,      lowerCamelCase							:		str							,      lowerCamelCase							:		Optional[str] = None	)			->				Tuple[str]:
        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(lowerCamelCase	):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory"	)
               return
        _UpperCamelCase  :							List[str]	    =	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	):
               copyfile(self.vocab_file							,      lowerCamelCase	)

        return (out_vocab_file,)




"""simple docstring"""







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







     '''simple docstring'''


     if not isinstance(_SCREAMING_SNAKE_CASE  ,       _SCREAMING_SNAKE_CASE						) or not all(
         isinstance(_SCREAMING_SNAKE_CASE  ,       _SCREAMING_SNAKE_CASE						) and item >= 0 for item in citations						):
          raise ValueError('The citations should be a list of non negative integers.'						)

     citations.sort()
     __A					:					Any								=		len(_SCREAMING_SNAKE_CASE						)

     for i in range(_SCREAMING_SNAKE_CASE						):
          if citations[len_citations - 1 - i] <= i:
               return i

     return len_citations


if __name__ == "__main__":
       import doctest

       doctest.testmod()



