






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


UpperCAmelCase__				   =		logging.get_logger(__name__)

UpperCAmelCase__				   =		{"tokenizer_file": "tokenizer.json"}

UpperCAmelCase__				   =		{
    "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 		lowercase_					(	lowercase   ):






      '''simple docstring'''




      __snake_case       =  VOCAB_FILES_NAMES
      __snake_case       =  PRETRAINED_VOCAB_FILES_MAP
      __snake_case       =  ['''input_ids''', '''attention_mask''']
      __snake_case       =  None







      def __init__(      self      :						Dict ,					__UpperCAmelCase      :						str=None ,					__UpperCAmelCase      :						Dict=None ,					__UpperCAmelCase      :						Dict=None ,					__UpperCAmelCase      :						int="<unk>" ,					__UpperCAmelCase      :						str="<s>" ,					__UpperCAmelCase      :						str="</s>" ,					__UpperCAmelCase      :						Dict="<pad>" ,					__UpperCAmelCase      :						Optional[int]=False ,					__UpperCAmelCase      :						Union[str, Any]=False ,					**__UpperCAmelCase      :						Optional[int] ,					)    ->List[Any]:




       """simple docstring"""


       super().__init__(
           __UpperCAmelCase ,					__UpperCAmelCase ,					tokenizer_file=__UpperCAmelCase ,					unk_token=__UpperCAmelCase ,					bos_token=__UpperCAmelCase ,					eos_token=__UpperCAmelCase ,					pad_token=__UpperCAmelCase ,					add_prefix_space=__UpperCAmelCase ,					clean_up_tokenization_spaces=__UpperCAmelCase ,					**__UpperCAmelCase ,					)
       a		  =      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()  )
       if pre_tok_state.get('''add_prefix_space''' ,					__UpperCAmelCase  ) != add_prefix_space:
        a		  =      getattr(__UpperCAmelCase ,					pre_tok_state.pop('''type'''  )  )
        a		  =      add_prefix_space
        a		  =      pre_tok_class(**__UpperCAmelCase  )

       a		  =      add_prefix_space







      def       __lowerCAmelCase					(      self      :						Optional[int] ,					*__UpperCAmelCase      :						Optional[int] ,					**__UpperCAmelCase      :						int  )    ->BatchEncoding:




       """simple docstring"""


       a		  =      kwargs.get('''is_split_into_words''' ,					__UpperCAmelCase  )
       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(*__UpperCAmelCase ,					**__UpperCAmelCase  )







      def       __lowerCAmelCase					(      self      :						Optional[int] ,					*__UpperCAmelCase      :						Tuple ,					**__UpperCAmelCase      :						Optional[int]  )    ->BatchEncoding:




       """simple docstring"""


       a		  =      kwargs.get('''is_split_into_words''' ,					__UpperCAmelCase  )

       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(*__UpperCAmelCase ,					**__UpperCAmelCase  )







      def       __lowerCAmelCase					(      self      :						Union[str, Any] ,					__UpperCAmelCase      :						str ,					__UpperCAmelCase      :						Optional[str] = None  )    ->Tuple[str]:




       """simple docstring"""


       a		  =      self._tokenizer.model.save(__UpperCAmelCase ,					name=__UpperCAmelCase  )
       return tuple(__UpperCAmelCase  )







      def       __lowerCAmelCase					(      self      :						Optional[int] ,					__UpperCAmelCase      :						"Conversation"  )    ->List[int]:




       """simple docstring"""


       a		  =      []
       for is_user, text in conversation.iter_texts():
        input_ids.extend(self.encode(__UpperCAmelCase ,					add_special_tokens=__UpperCAmelCase  ) + [self.eos_token_id]  )

       if len(__UpperCAmelCase  ) > self.model_max_length:
        a		  =      input_ids[-self.model_max_length :]
       return input_ids










def 						_a    (      a :int = 100 )							->			int:
 a		  =      n * (n + 1) * (2 * n + 1) / 6
 a		  =      (n * (n + 1) / 2) ** 2
 return int(square_of_sum - sum_of_squares )


if __name__ == "__main__":
     print(f"""{solution() = }""")


