import json
from typing import TYPE_CHECKING, List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_deberta import DebertaTokenizer


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation


UpperCAmelCase     						=			logging.get_logger(__name__)

UpperCAmelCase     						=			{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCAmelCase     						=			{
    '''vocab_file''': {
        '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json''',
        '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json''',
        '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json''',
        '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json''',
        '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json''',
        '''microsoft/deberta-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'''
        ),
    },
    '''merges_file''': {
        '''microsoft/deberta-base''': '''https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt''',
        '''microsoft/deberta-large''': '''https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt''',
        '''microsoft/deberta-xlarge''': '''https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt''',
        '''microsoft/deberta-base-mnli''': '''https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt''',
        '''microsoft/deberta-large-mnli''': '''https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt''',
        '''microsoft/deberta-xlarge-mnli''': (
            '''https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'''
        ),
    },
}

UpperCAmelCase     						=			{
    '''microsoft/deberta-base''': 5_12,
    '''microsoft/deberta-large''': 5_12,
    '''microsoft/deberta-xlarge''': 5_12,
    '''microsoft/deberta-base-mnli''': 5_12,
    '''microsoft/deberta-large-mnli''': 5_12,
    '''microsoft/deberta-xlarge-mnli''': 5_12,
}

UpperCAmelCase     						=			{
    '''microsoft/deberta-base''': {'''do_lower_case''': False},
    '''microsoft/deberta-large''': {'''do_lower_case''': False},
}




class 				__lowerCAmelCase					(    a_  ):



 '''simple docstring'''
 _lowerCamelCase  :		List[Any]			      =	VOCAB_FILES_NAMES
 _lowerCamelCase  :		str			      =	PRETRAINED_VOCAB_FILES_MAP
 _lowerCamelCase  :		Tuple			      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCamelCase  :		str			      =	['input_ids', 'attention_mask', 'token_type_ids']
 _lowerCamelCase  :		Dict			      =	DebertaTokenizer

 def __init__(     self    :						List[Any]    ,     lowerCamelCase    :						List[str]=None    ,     lowerCamelCase    :						str=None    ,     lowerCamelCase    :						Tuple=None    ,     lowerCamelCase    :						Optional[Any]="replace"    ,     lowerCamelCase    :						Optional[Any]="[CLS]"    ,     lowerCamelCase    :						Dict="[SEP]"    ,     lowerCamelCase    :						Any="[SEP]"    ,     lowerCamelCase    :						str="[CLS]"    ,     lowerCamelCase    :						Tuple="[UNK]"    ,     lowerCamelCase    :						str="[PAD]"    ,     lowerCamelCase    :						Optional[int]="[MASK]"    ,     lowerCamelCase    :						Optional[int]=False    ,     **lowerCamelCase    :						List[Any]    ,     )	->							Optional[Any]:
        super().__init__(
            lowerCamelCase    ,     lowerCamelCase    ,     tokenizer_file=lowerCamelCase    ,     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    ,     )
        _UpperCamelCase       :    Optional[Any]					  =					kwargs.pop('add_bos_token'    ,     lowerCamelCase					)

        _UpperCamelCase       :    str					  =					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()					)
        if pre_tok_state.get('add_prefix_space'    ,     lowerCamelCase					) != add_prefix_space:
               _UpperCamelCase       :    int					  =					getattr(lowerCamelCase    ,     pre_tok_state.pop('type'					)					)
               _UpperCamelCase       :    int					  =					add_prefix_space
               _UpperCamelCase       :    int					  =					pre_tok_class(**lowerCamelCase					)

        _UpperCamelCase       :    Union[str, Any]					  =					add_prefix_space

 @property
 def    __snake_case   (     self    :						List[str]					)	->							str:
        if self._mask_token is None:
               if self.verbose:
                      logger.error('Using mask_token, but it is not set yet.'					)
               return None
        return str(self._mask_token					)

 @mask_token.setter
 def    __snake_case   (     self    :						Optional[int]    ,     lowerCamelCase    :						Union[str, Any]					)	->							Optional[Any]:
        _UpperCamelCase       :    Tuple					  =					AddedToken(lowerCamelCase    ,     lstrip=lowerCamelCase    ,     rstrip=lowerCamelCase					) if isinstance(lowerCamelCase    ,     lowerCamelCase					) else value
        _UpperCamelCase       :    Optional[Any]					  =					value

 def    __snake_case   (     self    :						Tuple    ,     lowerCamelCase    :						List[int]    ,     lowerCamelCase    :						Optional[List[int]] = None					)	->							List[int]:
        if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        _UpperCamelCase       :    str					  =					[self.cls_token_id]
        _UpperCamelCase       :    Tuple					  =					[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep

 def    __snake_case   (     self    :						Any    ,     lowerCamelCase    :						List[int]    ,     lowerCamelCase    :						Optional[List[int]] = None					)	->							List[int]:
        _UpperCamelCase       :    Optional[int]					  =					[self.sep_token_id]
        _UpperCamelCase       :    Optional[Any]					  =					[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    :						str    ,     *lowerCamelCase    :						List[str]    ,     **lowerCamelCase    :						int					)	->							BatchEncoding:
        _UpperCamelCase       :    Dict					  =					kwargs.get('is_split_into_words'    ,     lowerCamelCase					)
        assert self.add_prefix_space or not is_split_into_words, (
            f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
            "to use it with pretokenized inputs."
        )

        return super()._batch_encode_plus(*lowerCamelCase    ,     **lowerCamelCase					)

 def    __snake_case   (     self    :						Dict    ,     *lowerCamelCase    :						Optional[int]    ,     **lowerCamelCase    :						List[Any]					)	->							BatchEncoding:
        _UpperCamelCase       :    List[Any]					  =					kwargs.get('is_split_into_words'    ,     lowerCamelCase					)

        assert self.add_prefix_space or not is_split_into_words, (
            f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
            "to use it with pretokenized inputs."
        )

        return super()._encode_plus(*lowerCamelCase    ,     **lowerCamelCase					)

 def    __snake_case   (     self    :						Union[str, Any]    ,     lowerCamelCase    :						str    ,     lowerCamelCase    :						Optional[str] = None					)	->							Tuple[str]:
        _UpperCamelCase       :    Any					  =					self._tokenizer.model.save(lowerCamelCase    ,     name=lowerCamelCase					)
        return tuple(lowerCamelCase					)

 def    __snake_case   (     self    :						str    ,     lowerCamelCase    :						"Conversation"					)	->							List[int]:
        _UpperCamelCase       :    Tuple					  =					[]
        for is_user, text in conversation.iter_texts():
               input_ids.extend(self.encode(lowerCamelCase    ,     add_special_tokens=lowerCamelCase					) + [self.eos_token_id]					)

        if len(lowerCamelCase					) > self.model_max_length:
               _UpperCamelCase       :    List[str]					  =					input_ids[-self.model_max_length :]
        return input_ids




def SCREAMING_SNAKE_CASE			(       lowercase_:		list[int]			):

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

       citations.sort()
       _UpperCamelCase       :    List[str]					  =					len(lowercase_			)

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

       return len_citations


if __name__ == "__main__":
 import doctest

 doctest.testmod()



