





'''simple docstring'''
import os
from shutil import copyfile
from typing import TYPE_CHECKING, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
from ...utils.versions import require_version


if TYPE_CHECKING:
    from transformers.pipelines.conversational import Conversation

require_version('''tokenizers>=0.13.3''')

if is_sentencepiece_available():
    from .tokenization_llama import LlamaTokenizer
else:
    a__							:							Dict			=None

a__							:							Tuple			=logging.get_logger(__name__)
a__							:							Optional[Any]			={'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}

a__							:							Dict			='[INST]', '[/INST]'
a__							:							int			='<<SYS>>\n', '\n<</SYS>>\n\n'

# fmt: off
a__							:							Optional[int]			='You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\\nanswers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\\nthat your responses are socially unbiased and positive in nature.\n\nIf a question does not make any sense, or is not factually coherent, explain why instead of answering something not\\ncorrect. If you don\'t know the answer to a question, please don\'t share false information.'

class 					snake_case					(   UpperCAmelCase_	):




 """simple docstring"""



 SCREAMING_SNAKE_CASE_     : str      		=VOCAB_FILES_NAMES
 SCREAMING_SNAKE_CASE_     : Optional[Any]      		=LlamaTokenizer
 SCREAMING_SNAKE_CASE_     : Any      		="left"
 SCREAMING_SNAKE_CASE_     : Dict      		=["input_ids", "attention_mask"]






 def __init__(	self	:							Optional[Any]							,     __A	:							Union[str, Any]=None							,     __A	:							Optional[Any]=None							,     __A	:							int=False							,     __A	:							Tuple="<unk>"							,     __A	:							Optional[Any]="<s>"							,     __A	:							Any="</s>"							,     __A	:							Tuple=True							,     __A	:							Tuple=False							,     **__A	:							Tuple							,     ):
        super().__init__(
            vocab_file=__UpperCamelCase							,     tokenizer_file=__UpperCamelCase							,     clean_up_tokenization_spaces=__UpperCamelCase							,     unk_token=__UpperCamelCase							,     bos_token=__UpperCamelCase							,     eos_token=__UpperCamelCase							,     **__UpperCamelCase							,     )
        __UpperCamelCase	=  add_bos_token
        __UpperCamelCase	=  add_eos_token
        self.update_post_processor()

        __UpperCamelCase	=  vocab_file
        __UpperCamelCase	=  False if not self.vocab_file else True






 def 	_lowerCamelCase (	self	:							Tuple     ):
        __UpperCamelCase	=  self.bos_token
        __UpperCamelCase	=  self.bos_token_id

        __UpperCamelCase	=  self.eos_token
        __UpperCamelCase	=  self.eos_token_id

        __UpperCamelCase	=  f'''{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}'''
        __UpperCamelCase	=  f'''{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}'''

        __UpperCamelCase	=  []
        if self.add_bos_token:
               special_tokens.append((bos, bos_token_id)     )
        if self.add_eos_token:
               special_tokens.append((eos, eos_token_id)     )
        __UpperCamelCase	=  processors.TemplateProcessing(
            single=__UpperCamelCase							,     pair=__UpperCamelCase							,     special_tokens=__UpperCamelCase     )






 @property
 def 	_lowerCamelCase (	self	:							Optional[Any]     ):
        return self._add_eos_token






 @property
 def 	_lowerCamelCase (	self	:							Optional[int]     ):
        return self._add_bos_token






 @add_eos_token.setter
 def 	_lowerCamelCase (	self	:							str							,     __A	:							Optional[int]     ):
        __UpperCamelCase	=  value
        self.update_post_processor()






 @add_bos_token.setter
 def 	_lowerCamelCase (	self	:							Optional[Any]							,     __A	:							str     ):
        __UpperCamelCase	=  value
        self.update_post_processor()






 def 	_lowerCamelCase (	self	:							Union[str, Any]							,     __A	:							Any							,     __A	:							Optional[int] = None     ):
        if not self.can_save_slow_tokenizer:
               raise ValueError(
                   'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
                   'tokenizer.'     )

        if not os.path.isdir(__UpperCamelCase     ):
               logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
               return
        __UpperCamelCase	=  os.path.join(
            __UpperCamelCase							,     (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )

        if os.path.abspath(self.vocab_file     ) != os.path.abspath(__UpperCamelCase     ):
               copyfile(self.vocab_file							,     __UpperCamelCase     )

        return (out_vocab_file,)






 def 	_lowerCamelCase (	self	:							List[Any]							,     __A	:							int     ):
        __UpperCamelCase	=  list(conversation.iter_texts()     )
        if not all([is_user for is_user, msg in dialogue[::2]]     ) or not all(
            [not is_user for is_user, msg in dialogue[1::2]]     ):
               raise ValueError(
                   'The model only supports \'user\' and \'assistant\' roles, starting with user and alternating (u/a/u/a/u...)'     )

        __UpperCamelCase	=  []
        if len(conversation.past_user_inputs     ) > 0:
               if not conversation.past_user_inputs[0].startswith(__UpperCamelCase     ) or E_SYS not in conversation.past_user_inputs[0]:
                      __UpperCamelCase	=  (
                          B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
                      )
        elif not dialogue[0][1].startswith(__UpperCamelCase     ) or E_SYS not in dialogue[0][1]:
               __UpperCamelCase	=  (dialogue[0][0], B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + dialogue[0][1])

        dialog_tokens += sum(
            [
                [self.bos_token_id]
                + self.encode(
                    f'''{B_INST} {(prompt[1]).strip()} {E_INST} {(answer[1]).strip()} '''							,     add_special_tokens=__UpperCamelCase     )
                + [self.eos_token_id]
                for prompt, answer in zip(dialogue[::2]							,     dialogue[1::2]     )
            ]							,     []							,     )
        if not (dialogue[-1][0]):
               raise ValueError(f'''Last message must be from user, got {dialogue[-1]['role']}'''     )
        dialog_tokens += [self.bos_token_id] + self.encode(
            f'''{B_INST} {(dialogue[-1][1]).strip()} {E_INST}'''							,     add_special_tokens=__UpperCamelCase     )
        return dialog_tokens











'''simple docstring'''
def     lowercase__       (       __lowercase						:  int = 20					)			->				int:



       """simple docstring"""






       try:
              __UpperCamelCase	=  int(__lowercase					)
       except (TypeError, ValueError):
              raise TypeError('Parameter n must be int or castable to int.'					)
       if n <= 0:
              raise ValueError('Parameter n must be greater than or equal to one.'					)
       __UpperCamelCase	=  0
       while 1:
              i += n * (n - 1)
              __UpperCamelCase	=  0
              for j in range(2    ,  __lowercase					):
                     if i % j != 0:
                            __UpperCamelCase	=  1
                            break
              if nfound == 0:
                     if i == 0:
                            __UpperCamelCase	=  1
                     return i
       return None


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