




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

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import BlenderbotTokenizer


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

_lowerCamelCase     					=		logging.get_logger(__name__)


_lowerCamelCase     					=		{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

_lowerCamelCase     					=		{
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

_lowerCamelCase     					=		{'''facebook/blenderbot-3B''': 1_28}



class      a	(  _A     ):

     '''simple docstring'''





     lowerCAmelCase							:			Dict  						=    VOCAB_FILES_NAMES
     lowerCAmelCase							:			Union[str, Any]  						=    PRETRAINED_VOCAB_FILES_MAP
     lowerCAmelCase							:			int  						=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     lowerCAmelCase							:			int  						=    ['input_ids', 'attention_mask']
     lowerCAmelCase							:			int  						=    BlenderbotTokenizer
     def __init__(      self  :     str   ,       __snake_case  :     Any=None   ,       __snake_case  :     List[str]=None   ,       __snake_case  :     str=None   ,       __snake_case  :     Optional[Any]="replace"   ,       __snake_case  :     List[str]="<s>"   ,       __snake_case  :     int="</s>"   ,       __snake_case  :     Optional[Any]="</s>"   ,       __snake_case  :     Optional[int]="<s>"   ,       __snake_case  :     Union[str, Any]="<unk>"   ,       __snake_case  :     Union[str, Any]="<pad>"   ,       __snake_case  :     List[Any]="<mask>"   ,       __snake_case  :     Tuple=False   ,       __snake_case  :     Optional[Any]=True   ,       **__snake_case  :     Any   ,       ):
         super().__init__(
             _lowerCAmelCase   ,       _lowerCAmelCase   ,       tokenizer_file=_lowerCAmelCase   ,       errors=_lowerCAmelCase   ,       bos_token=_lowerCAmelCase   ,       eos_token=_lowerCAmelCase   ,       sep_token=_lowerCAmelCase   ,       cls_token=_lowerCAmelCase   ,       unk_token=_lowerCAmelCase   ,       pad_token=_lowerCAmelCase   ,       mask_token=_lowerCAmelCase   ,       add_prefix_space=_lowerCAmelCase   ,       trim_offsets=_lowerCAmelCase   ,       **_lowerCAmelCase   ,       )

         UpperCAmelCase_									=	json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
         if pre_tok_state.get('''add_prefix_space'''   ,       _lowerCAmelCase							) != add_prefix_space:
             UpperCAmelCase_									=	getattr(_lowerCAmelCase   ,       pre_tok_state.pop('''type'''							)							)
             UpperCAmelCase_									=	add_prefix_space
             UpperCAmelCase_									=	pre_tok_class(**_lowerCAmelCase							)

         UpperCAmelCase_									=	add_prefix_space

         UpperCAmelCase_									=	'''post_processor'''
         UpperCAmelCase_									=	getattr(self.backend_tokenizer   ,       _lowerCAmelCase   ,       _lowerCAmelCase							)
         if tokenizer_component_instance:
             UpperCAmelCase_									=	json.loads(tokenizer_component_instance.__getstate__()							)

             # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
             if "sep" in state:
                 UpperCAmelCase_									=	tuple(state['''sep''']							)
             if "cls" in state:
                 UpperCAmelCase_									=	tuple(state['''cls''']							)

             UpperCAmelCase_									=	False

             if state.get('''add_prefix_space'''   ,       _lowerCAmelCase							) != add_prefix_space:
                 UpperCAmelCase_									=	add_prefix_space
                 UpperCAmelCase_									=	True

             if state.get('''trim_offsets'''   ,       _lowerCAmelCase							) != trim_offsets:
                 UpperCAmelCase_									=	trim_offsets
                 UpperCAmelCase_									=	True

             if changes_to_apply:
                 UpperCAmelCase_									=	getattr(_lowerCAmelCase   ,       state.pop('''type'''							)							)
                 UpperCAmelCase_									=	component_class(**_lowerCAmelCase							)
                 setattr(self.backend_tokenizer   ,       _lowerCAmelCase   ,       _lowerCAmelCase							)
     @property
     # Copied from transformers.models.roberta.tokenization_roberta_fast.RobertaTokenizerFast.mask_token with Roberta->Blenderbot, RoBERTa->Blenderbot
     def     lowerCamelCase_  (      self  :     Optional[int]							):
         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     lowerCamelCase_  (      self  :     Dict   ,       __snake_case  :     Union[str, Any]							):
         UpperCAmelCase_									=	AddedToken(_lowerCAmelCase   ,       lstrip=_lowerCAmelCase   ,       rstrip=_lowerCAmelCase							) if isinstance(_lowerCAmelCase   ,       _lowerCAmelCase							) else value
         UpperCAmelCase_									=	value
     def     lowerCamelCase_  (      self  :     List[Any]   ,       *__snake_case  :     Dict   ,       **__snake_case  :     List[str]							):
         UpperCAmelCase_									=	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     lowerCamelCase_  (      self  :     Dict   ,       *__snake_case  :     Optional[int]   ,       **__snake_case  :     Optional[Any]							):
         UpperCAmelCase_									=	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     lowerCamelCase_  (      self  :     Optional[Any]   ,       __snake_case  :     str   ,       __snake_case  :     Optional[str] = None							):
         UpperCAmelCase_									=	self._tokenizer.model.save(_lowerCAmelCase   ,       name=_lowerCAmelCase							)
         return tuple(_lowerCAmelCase							)
     def     lowerCamelCase_  (      self  :     Tuple   ,       __snake_case  :     List[int]   ,       __snake_case  :     Optional[List[int]] = None							):
         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  :     List[str]   ,       __snake_case  :     List[int]   ,       __snake_case  :     Optional[List[int]] = None							):
         return token_ids_a + [self.eos_token_id]




     def     lowerCamelCase_  (      self  :     Union[str, Any]   ,       __snake_case  :     "Conversation"							):
         UpperCAmelCase_									=	[]
         for is_user, text in conversation.iter_texts():
             if is_user:
                 # We need to space prefix as it's being done within blenderbot
                 inputs.append(''' ''' + text							)
             else:
                 # Generated responses should contain them already.
                 inputs.append(_lowerCAmelCase							)

         UpperCAmelCase_									=	'''  '''.join(_lowerCAmelCase							)
         UpperCAmelCase_									=	self.encode(_lowerCAmelCase							)
         if len(_lowerCAmelCase							) > self.model_max_length:
             UpperCAmelCase_									=	input_ids[-self.model_max_length :]
             logger.warning(F'Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'							)
         return input_ids









def       _lowerCAmelCase    (				lowerCAmelCase_				:List[str]		,    lowerCAmelCase_				:int				)->Optional[int]:
   '''simple docstring'''






   snake_case_            =       0
   while b > 0:
      if b & 1:
         res += a

      a += a
      b >>= 1

   return res



def       _lowerCAmelCase    (				lowerCAmelCase_				:int		,    lowerCAmelCase_				:List[str]		,    lowerCAmelCase_				:Dict				)->Dict:
   '''simple docstring'''






   snake_case_            =       0
   while b > 0:
      if b & 1:
         snake_case_            =       ((res % c) + (a % c)) % c

      a += a
      b >>= 1

   return res




