





def    __snake_case  (    _lowerCAmelCase       :       int		)       ->  str:
   A_    : int								=	int(lowerCAmelCase__		)
   if decimal in (0, 1):  # Exit cases for the recursion
      return str(lowerCAmelCase__		)
   A_    : List[Any]								=	divmod(lowerCAmelCase__ , 2		)
   return binary_recursive(lowerCAmelCase__		) + str(lowerCAmelCase__		)

def    __snake_case  (    _lowerCAmelCase       :       str		)       ->  str:
   A_    : int								=	str(lowerCAmelCase__		).strip()
   if not number:
      raise ValueError("No input value was provided"		)
   A_    : str								=	'-' if number.startswith("-"		) else ''
   A_    : Union[str, Any]								=	number.lstrip("-"		)
   if not number.isnumeric():
      raise ValueError("Input value is not an integer"		)
   return f"{negative}0b{binary_recursive(int(lowerCAmelCase__		)		)}"


if __name__ == "__main__":
 from doctest import testmod

 testmod()





"""simple docstring"""







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

from tokenizers import pre_tokenizers

from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if TYPE_CHECKING:
     from transformers.pipelines.conversational import Conversation


lowercase__		:				Optional[Any]          =	logging.get_logger(__name__)

lowercase__		:				List[str]          =	{"""tokenizer_file""": """tokenizer.json"""}

lowercase__		:				List[str]          =	{
    """tokenizer_file""": {
        """bigscience/tokenizer""": """https://huggingface.co/bigscience/tokenizer/blob/main/tokenizer.json""",
        """bigscience/bloom-560m""": """https://huggingface.co/bigscience/bloom-560m/blob/main/tokenizer.json""",
        """bigscience/bloom-1b1""": """https://huggingface.co/bigscience/bloom-1b1/blob/main/tokenizer.json""",
        """bigscience/bloom-1b7""": """https://huggingface.co/bigscience/bloom-1b7/blob/main/tokenizer.json""",
        """bigscience/bloom-3b""": """https://huggingface.co/bigscience/bloom-3b/blob/main/tokenizer.json""",
        """bigscience/bloom-7b1""": """https://huggingface.co/bigscience/bloom-7b1/blob/main/tokenizer.json""",
        """bigscience/bloom""": """https://huggingface.co/bigscience/bloom/blob/main/tokenizer.json""",
    },
}







class       UpperCamelCase__   (	lowercase_  ):




      """simple docstring"""




      _SCREAMING_SNAKE_CASE  				=     VOCAB_FILES_NAMES
      _SCREAMING_SNAKE_CASE  				=     PRETRAINED_VOCAB_FILES_MAP
      _SCREAMING_SNAKE_CASE  				=     ["""input_ids""", """attention_mask"""]
      _SCREAMING_SNAKE_CASE  				=     None



      def __init__(      self				:      Union[str, Any]    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]=None    ,			SCREAMING_SNAKE_CASE_				:      Optional[Any]=None    ,			SCREAMING_SNAKE_CASE_				:      Tuple=None    ,			SCREAMING_SNAKE_CASE_				:      Optional[Any]="<unk>"    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]="<s>"    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]="</s>"    ,			SCREAMING_SNAKE_CASE_				:      Optional[int]="<pad>"    ,			SCREAMING_SNAKE_CASE_				:      List[str]=False    ,			SCREAMING_SNAKE_CASE_				:      Any=False    ,			**SCREAMING_SNAKE_CASE_				:      Any    ,			):
        super().__init__(
            SCREAMING_SNAKE_CASE_    ,			SCREAMING_SNAKE_CASE_    ,			tokenizer_file=SCREAMING_SNAKE_CASE_    ,			unk_token=SCREAMING_SNAKE_CASE_    ,			bos_token=SCREAMING_SNAKE_CASE_    ,			eos_token=SCREAMING_SNAKE_CASE_    ,			pad_token=SCREAMING_SNAKE_CASE_    ,			add_prefix_space=SCREAMING_SNAKE_CASE_    ,			clean_up_tokenization_spaces=SCREAMING_SNAKE_CASE_    ,			**SCREAMING_SNAKE_CASE_    ,			)
        lowerCAmelCase_   :				Optional[Any]								= json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
        if pre_tok_state.get('add_prefix_space'    ,			SCREAMING_SNAKE_CASE_       ) != add_prefix_space:
          lowerCAmelCase_   :				str								= getattr(SCREAMING_SNAKE_CASE_    ,			pre_tok_state.pop('type'       )       )
          lowerCAmelCase_   :				str								= add_prefix_space
          lowerCAmelCase_   :				str								= pre_tok_class(**SCREAMING_SNAKE_CASE_       )

        lowerCAmelCase_   :				str								= add_prefix_space



      def      SCREAMING_SNAKE_CASE__ (      self				:      Any    ,			*SCREAMING_SNAKE_CASE_				:      List[Any]    ,			**SCREAMING_SNAKE_CASE_				:      Tuple       ):
        lowerCAmelCase_   :				List[Any]								= kwargs.get('is_split_into_words'    ,			SCREAMING_SNAKE_CASE_       )
        if not (self.add_prefix_space or not is_split_into_words):
          raise Exception(
              F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
              ' pretokenized inputs.'       )

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



      def      SCREAMING_SNAKE_CASE__ (      self				:      Any    ,			*SCREAMING_SNAKE_CASE_				:      Optional[int]    ,			**SCREAMING_SNAKE_CASE_				:      int       ):
        lowerCAmelCase_   :				List[Any]								= kwargs.get('is_split_into_words'    ,			SCREAMING_SNAKE_CASE_       )

        if not (self.add_prefix_space or not is_split_into_words):
          raise Exception(
              F"You need to instantiate {self.__class__.__name__} with add_prefix_space=True to use it with"
              ' pretokenized inputs.'       )

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



      def      SCREAMING_SNAKE_CASE__ (      self				:      Optional[Any]    ,			SCREAMING_SNAKE_CASE_				:      str    ,			SCREAMING_SNAKE_CASE_				:      Optional[str] = None       ):
        lowerCAmelCase_   :				Optional[int]								= self._tokenizer.model.save(SCREAMING_SNAKE_CASE_    ,			name=SCREAMING_SNAKE_CASE_       )
        return tuple(SCREAMING_SNAKE_CASE_       )





      def      SCREAMING_SNAKE_CASE__ (      self				:      int    ,			SCREAMING_SNAKE_CASE_				:      "Conversation"       ):
        lowerCAmelCase_   :				int								= []
        for is_user, text in conversation.iter_texts():
          input_ids.extend(self.encode(SCREAMING_SNAKE_CASE_    ,			add_special_tokens=SCREAMING_SNAKE_CASE_       ) + [self.eos_token_id]       )

        if len(SCREAMING_SNAKE_CASE_       ) > self.model_max_length:
          lowerCAmelCase_   :				Any								= input_ids[-self.model_max_length :]
        return input_ids





