code: 
  
  
  
  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:
      __lowerCamelCase  				=					None
  
  __lowerCamelCase  				=					logging.get_logger(__name__)
  __lowerCamelCase  				=					{"""vocab_file""": """tokenizer.model""", """tokenizer_file""": """tokenizer.json"""}
  
  __lowerCamelCase				,				__lowerCamelCase  				=					"""[INST]""", """[/INST]"""
  __lowerCamelCase				,				__lowerCamelCase  				=					"""<<SYS>>\n""", """\n<</SYS>>\n\n"""
  
  # fmt: off
  __lowerCamelCase  				=					"""You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your\
  answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure\
  that your responses are socially unbiased and positive in nature.
  
  If a question does not make any sense, or is not factually coherent, explain why instead of answering something not\
  correct. If you don't know the answer to a question, please don't share false information."""
  
  
  
  class 		_snake_case      (			lowerCamelCase				):
  
  
  
  
  
    """simple docstring"""
  
  
  
    lowerCamelCase_          =			VOCAB_FILES_NAMES
    lowerCamelCase_          =			LlamaTokenizer
    lowerCamelCase_          =			'''left'''
    lowerCamelCase_          =			['''input_ids''', '''attention_mask''']
    def __init__(						self	,    a=None	,    a=None	,    a=False	,    a="<unk>"	,    a="<s>"	,    a="</s>"	,    a=True	,    a=False	,    **a	,    )	->							int:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      super().__init__(
          vocab_file=a	,    tokenizer_file=a	,    clean_up_tokenization_spaces=a	,    unk_token=a	,    bos_token=a	,    eos_token=a	,    **a	,    )
      _A           =    add_bos_token
      _A           =    add_eos_token
      self.update_post_processor()
  
      _A           =    vocab_file
      _A           =    False if not self.vocab_file else True
    def lowercase_		(						self					)	->							int:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      _A           =    self.bos_token
      _A           =    self.bos_token_id
  
      _A           =    self.eos_token
      _A           =    self.eos_token_id
  
      _A           =    f'''{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}'''
      _A           =    f'''{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}'''
  
      _A           =    []
      if self.add_bos_token:
        special_tokens.append((bos, bos_token_id)					)
      if self.add_eos_token:
        special_tokens.append((eos, eos_token_id)					)
      _A           =    processors.TemplateProcessing(
          single=a	,    pair=a	,    special_tokens=a					)
    @property
    def lowercase_		(						self					)	->							int:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      return self._add_eos_token
    @property
    def lowercase_		(						self					)	->							Optional[int]:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      return self._add_bos_token
    @add_eos_token.setter
    def lowercase_		(						self	,    a					)	->							Union[str, Any]:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      _A           =    value
      self.update_post_processor()
    @add_bos_token.setter
    def lowercase_		(						self	,    a					)	->							int:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      _A           =    value
      self.update_post_processor()
    def lowercase_		(						self	,    a	,    a = None					)	->							Tuple[str]:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      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(a					):
        logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''					)
        return
      _A           =    os.path.join(
          a	,    (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)
  
      if os.path.abspath(self.vocab_file					) != os.path.abspath(a					):
        copyfile(self.vocab_file	,    a					)
  
      return (out_vocab_file,)
  
  
  
    def lowercase_		(						self	,    a					)	->							int:
  
  
  
  
      """simple docstring"""
  
  
  
  
  
  
  
      _A           =    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...)'''					)
  
      _A           =    []
      if len(conversation.past_user_inputs					) > 0:
        if not conversation.past_user_inputs[0].startswith(a					) or E_SYS not in conversation.past_user_inputs[0]:
          _A           =    (
              B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
          )
      elif not dialogue[0][1].startswith(a					) or E_SYS not in dialogue[0][1]:
        _A           =    (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=a					)
              + [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=a					)
      return dialog_tokens
style_context: 
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				__snake_case							)   -> None:
    if target == 0:
      answer.append(path.copy()							)
    else:
      for index in range(__snake_case						,				len(__snake_case							)							):
        if target >= candidates[index]:
          path.append(candidates[index]							)
          backtrack(__snake_case						,				__snake_case						,				__snake_case						,				target - candidates[index]						,				__snake_case							)
          path.pop(len(__snake_case							) - 1							)
  
  
  
  
  def     UpperCAmelCase__ (							__snake_case						,				__snake_case							)   -> list:
    _A           =    []  # type: list[int]
    _A           =    []  # type: list[int]
    backtrack(__snake_case						,				__snake_case						,				__snake_case						,				__snake_case						,				0							)
    return answer
  
  
  
  
  def     UpperCAmelCase__ (							)   -> None:
    print(combination_sum([-8, 2.3, 0]						,				1							)							)
  
  
  if __name__ == "__main__":
      import doctest
  
      doctest.testmod()
      main()