



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


__snake_case		:Union[str, Any]   	=  logging.get_logger(__name__)

__snake_case		:Optional[int]   	=  {'''tokenizer_file''': '''tokenizer.json'''}

__snake_case		:Optional[int]   	=  {
    '''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 					_A (			__UpperCAmelCase					):
       UpperCamelCase__						:					Any		      =		VOCAB_FILES_NAMES
       UpperCamelCase__						:					Optional[Any]		      =		PRETRAINED_VOCAB_FILES_MAP
       UpperCamelCase__						:					str		      =		['''input_ids''', '''attention_mask''']
       UpperCamelCase__						:					Optional[Any]		      =		None



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


           '''simple docstring'''

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

           __a		 =       add_prefix_space



       def 	_lowerCamelCase    (	self							:  Dict  ,	*__SCREAMING_SNAKE_CASE							:  str  ,	**__SCREAMING_SNAKE_CASE							:  Tuple):


           '''simple docstring'''

           __a		 =       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 	_lowerCamelCase    (	self							:  str  ,	*__SCREAMING_SNAKE_CASE							:  List[Any]  ,	**__SCREAMING_SNAKE_CASE							:  Union[str, Any]):


           '''simple docstring'''

           __a		 =       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 	_lowerCamelCase    (	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  str  ,	__SCREAMING_SNAKE_CASE							:  Optional[str] = None):


           '''simple docstring'''

           __a		 =       self._tokenizer.model.save(__SCREAMING_SNAKE_CASE  ,	name=__SCREAMING_SNAKE_CASE)
           return tuple(__SCREAMING_SNAKE_CASE)





       def 	_lowerCamelCase    (	self							:  Any  ,	__SCREAMING_SNAKE_CASE							:  "Conversation"):


           '''simple docstring'''

           __a		 =       []
           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:
               __a		 =       input_ids[-self.model_max_length :]
           return input_ids










def   __snake_case			(    _UpperCAmelCase     ,				_UpperCAmelCase = False       ):

    if not isinstance(_UpperCAmelCase     ,				_UpperCAmelCase       ):
        __a		 =       f'Expected string as input, found {type(_UpperCAmelCase       )}'
        raise ValueError(_UpperCAmelCase       )
    if not isinstance(_UpperCAmelCase     ,				_UpperCAmelCase       ):
        __a		 =       f'Expected boolean as use_pascal parameter, found {type(_UpperCAmelCase       )}'
        raise ValueError(_UpperCAmelCase       )

    __a		 =       input_str.split('''_'''       )

    __a		 =       0 if use_pascal else 1

    __a		 =       words[start_index:]

    __a		 =       [word[0].upper() + word[1:] for word in words_to_capitalize]

    __a		 =       '''''' if use_pascal else words[0]

    return "".join([initial_word, *capitalized_words]       )


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

 testmod()





