code: 
  
  
  
  
  
  import os
  from shutil import copyfile
  from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
  
  import sentencepiece as spm
  
  from ...tokenization_utils import AddedToken, PreTrainedTokenizer
  from ...utils import logging
  
  
  if TYPE_CHECKING:
       from transformers.pipelines.conversational import Conversation
  
  UpperCAmelCase			:			str	  = logging.get_logger(__name__)
  
  UpperCAmelCase			:			List[Any]	  = {"""vocab_file""": """tokenizer.model"""}
  
  UpperCAmelCase			:			Dict	  = {
      """vocab_file""": {
          """hf-internal-testing/llama-tokenizer""": """https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer.model""",
      },
      """tokenizer_file""": {
          """hf-internal-testing/llama-tokenizer""": """https://huggingface.co/hf-internal-testing/llama-tokenizer/resolve/main/tokenizer_config.json""",
      },
  }
  UpperCAmelCase			:			Optional[int]	  = {
      """hf-internal-testing/llama-tokenizer""": 2048,
  }
  UpperCAmelCase			:			Any	  = """▁"""
  
  UpperCAmelCase  ,			UpperCAmelCase			:			int	  = """[INST]""", """[/INST]"""
  UpperCAmelCase  ,			UpperCAmelCase			:			List[str]	  = """<<SYS>>\n""", """\n<</SYS>>\n\n"""
  
  # fmt: off
  UpperCAmelCase			:			List[str]	  = """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        __lowerCAmelCase (					UpperCamelCase__):
        _lowercase       :      Dict        =    VOCAB_FILES_NAMES
        _lowercase       :      Optional[Any]        =    PRETRAINED_VOCAB_FILES_MAP
        _lowercase       :      Optional[Any]        =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
        _lowercase       :      Dict        =    ["""input_ids""", """attention_mask"""]
  
  
  
  
  
  
  
        def __init__(					self	,   lowerCAmelCase__	,   lowerCAmelCase__="<unk>"	,   lowerCAmelCase__="<s>"	,   lowerCAmelCase__="</s>"	,   lowerCAmelCase__=None	,   lowerCAmelCase__ = None	,   lowerCAmelCase__=True	,   lowerCAmelCase__=False	,   lowerCAmelCase__=False	,   lowerCAmelCase__=True	,   **lowerCAmelCase__	,   )     ->		Optional[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Union[str, Any]            ={} if sp_model_kwargs is None else sp_model_kwargs
          a__			:      Union[str, Any]            =AddedToken(lowerCAmelCase__	,   lstrip=lowerCAmelCase__	,   rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__	,   lowerCAmelCase__							) else bos_token
          a__			:      Any            =AddedToken(lowerCAmelCase__	,   lstrip=lowerCAmelCase__	,   rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__	,   lowerCAmelCase__							) else eos_token
          a__			:      int            =AddedToken(lowerCAmelCase__	,   lstrip=lowerCAmelCase__	,   rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__	,   lowerCAmelCase__							) else unk_token
          a__			:      int            =AddedToken(lowerCAmelCase__	,   lstrip=lowerCAmelCase__	,   rstrip=lowerCAmelCase__							) if isinstance(lowerCAmelCase__	,   lowerCAmelCase__							) else pad_token
          super().__init__(
              bos_token=lowerCAmelCase__	,   eos_token=lowerCAmelCase__	,   unk_token=lowerCAmelCase__	,   pad_token=lowerCAmelCase__	,   add_bos_token=lowerCAmelCase__	,   add_eos_token=lowerCAmelCase__	,   sp_model_kwargs=self.sp_model_kwargs	,   clean_up_tokenization_spaces=lowerCAmelCase__	,   legacy=lowerCAmelCase__	,   **lowerCAmelCase__	,   )
          if legacy:
            logger.warning_once(
                F'''You are using the legacy behaviour of the {self.__class__}. This means that tokens that come after special tokens will not be properly handled. We recommend you to'''
                " read the related pull request available at https://github.com/huggingface/transformers/pull/24565"							)
          a__			:      Optional[Any]            =legacy
          a__			:      Optional[int]            =vocab_file
          a__			:      Optional[int]            =add_bos_token
          a__			:      Dict            =add_eos_token
          a__			:      Optional[Any]            =spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.Load(lowerCAmelCase__							)
  
  
  
  
  
  
  
        def __getstate__(					self							)     ->		int:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Optional[int]            =self.__dict__.copy()
          a__			:      int            =None
          a__			:      Union[str, Any]            =self.sp_model.serialized_model_proto()
          return state
  
  
  
  
  
  
  
        def __setstate__(					self	,   lowerCAmelCase__							)     ->		Union[str, Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Optional[Any]            =d
          a__			:      Optional[int]            =spm.SentencePieceProcessor(**self.sp_model_kwargs							)
          self.sp_model.LoadFromSerializedProto(self.sp_model_proto							)
  
  
  
  
  
  
  
        @property
        def      _lowercase						(					self							)     ->		str:
  
  
  
          '''simple docstring'''
  
  
  
  
          return self.sp_model.get_piece_size()
  
  
  
  
  
  
  
        def      _lowercase						(					self							)     ->		Any:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Union[str, Any]            ={self.convert_ids_to_tokens(lowerCAmelCase__							): i for i in range(self.vocab_size							)}
          vocab.update(self.added_tokens_encoder							)
          return vocab
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   **lowerCAmelCase__							)     ->		List[str]:
  
  
  
          '''simple docstring'''
  
  
  
  
          if not self.legacy:
            a__			:      Union[str, Any]            =SPIECE_UNDERLINE + text.replace(lowerCAmelCase__	,   " "							)
          return super().tokenize(lowerCAmelCase__	,   **lowerCAmelCase__							)
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		List[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          if not self.legacy:
            a__			:      Union[str, Any]            =text.startswith(lowerCAmelCase__							)
            if is_first:
              a__			:      Optional[int]            =text[1:]
  
          a__			:      Dict            =self.sp_model.encode(lowerCAmelCase__	,   out_type=lowerCAmelCase__							)
  
          if not self.legacy and not is_first and not text.startswith(" "							) and tokens[0].startswith(lowerCAmelCase__							):
            a__			:      Optional[int]            =([tokens[0][1:]] if len(tokens[0]							) > 1 else []) + tokens[1:]
          return tokens
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		Optional[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          return self.sp_model.piece_to_id(lowerCAmelCase__							)
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		Optional[Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Optional[Any]            =self.sp_model.IdToPiece(lowerCAmelCase__							)
          return token
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		Union[str, Any]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Union[str, Any]            =[]
          a__			:      Tuple            =""
          a__			:      int            =False
          for i, token in enumerate(lowerCAmelCase__							):
            # make sure that special tokens are not decoded using sentencepiece model
            if token in self.all_special_tokens:
              if not prev_is_special and i != 0:
                out_string += " "
              out_string += self.sp_model.decode(lowerCAmelCase__							) + token
              a__			:      Optional[int]            =True
              a__			:      List[str]            =[]
            else:
              current_sub_tokens.append(lowerCAmelCase__							)
              a__			:      List[Any]            =False
          out_string += self.sp_model.decode(lowerCAmelCase__							)
          return out_string
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__ = None							)     ->		Tuple[str]:
  
  
  
          '''simple docstring'''
  
  
  
  
          if not os.path.isdir(lowerCAmelCase__							):
            logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''							)
            return
          a__			:      Optional[Any]            =os.path.join(
              lowerCAmelCase__	,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]							)
  
          if os.path.abspath(self.vocab_file							) != os.path.abspath(lowerCAmelCase__							) and os.path.isfile(self.vocab_file							):
            copyfile(self.vocab_file	,   lowerCAmelCase__							)
          elif not os.path.isfile(self.vocab_file							):
            with open(lowerCAmelCase__	,   "wb"							) as fi:
              a__			:      Union[str, Any]            =self.sp_model.serialized_model_proto()
              fi.write(lowerCAmelCase__							)
  
          return (out_vocab_file,)
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__=None							)     ->		str:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Any            =[self.bos_token_id] if self.add_bos_token else []
          a__			:      List[Any]            =[self.eos_token_id] if self.add_eos_token else []
  
          a__			:      Dict            =bos_token_id + token_ids_a + eos_token_id
  
          if token_ids_a is not None:
            a__			:      Dict            =output + bos_token_id + token_ids_a + eos_token_id
  
          return output
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__ = None	,   lowerCAmelCase__ = False							)     ->		List[int]:
  
  
  
          '''simple docstring'''
  
  
  
  
          if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=lowerCAmelCase__	,   token_ids_a=lowerCAmelCase__	,   already_has_special_tokens=lowerCAmelCase__							)
  
          a__			:      Any            =[1] if self.add_bos_token else []
          a__			:      Any            =[1] if self.add_eos_token else []
  
          if token_ids_a is None:
            return bos_token_id + ([0] * len(lowerCAmelCase__							)) + eos_token_id
          return (
              bos_token_id
              + ([0] * len(lowerCAmelCase__							))
              + eos_token_id
              + bos_token_id
              + ([0] * len(lowerCAmelCase__							))
              + eos_token_id
          )
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__	,   lowerCAmelCase__ = None							)     ->		List[int]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      str            =[self.bos_token_id] if self.add_bos_token else []
          a__			:      Dict            =[self.eos_token_id] if self.add_eos_token else []
  
          a__			:      int            =[0] * len(bos_token_id + token_ids_a + eos_token_id							)
  
          if token_ids_a is not None:
            output += [1] * len(bos_token_id + token_ids_a + eos_token_id							)
  
          return output
  
  
  
  
  
  
  
        def      _lowercase						(					self	,   lowerCAmelCase__							)     ->		List[int]:
  
  
  
          '''simple docstring'''
  
  
  
  
          a__			:      Tuple            =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__			:      List[int]            =[]
          if len(conversation.past_user_inputs							) > 0:
            if not conversation.past_user_inputs[0].startswith(lowerCAmelCase__							) or E_SYS not in conversation.past_user_inputs[0]:
              a__			:      Dict            =(
                  B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
              )
          elif not dialogue[0][1].startswith(lowerCAmelCase__							) or E_SYS not in dialogue[0][1]:
            a__			:      Optional[Any]            =(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=lowerCAmelCase__							)
                  + [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=lowerCAmelCase__							)
          return dialog_tokens
  
  
  
  
  
  
  
style_context: 
  
  
  
  
  
  def   _A (	SCREAMING_SNAKE_CASE  :     int		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    barcode //= 10  # exclude the last digit
    a__			:      int            =False
    a__			:      List[str]            =0
  
    # extract and check each digit
    while barcode != 0:
      a__			:      Optional[Any]            =1 if checker else 3
      s += mult * (barcode % 10)
      barcode //= 10
      a__			:      Union[str, Any]            =not checker
  
    return (10 - (s % 10)) % 10
  def   _A (	SCREAMING_SNAKE_CASE  :     int		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    return len(str(SCREAMING_SNAKE_CASE		)		) == 13 and get_check_digit(SCREAMING_SNAKE_CASE		) == barcode % 10
  def   _A (	SCREAMING_SNAKE_CASE  :     str		):
  
  
  
  
  
    """simple docstring"""
  
  
  
    if str(SCREAMING_SNAKE_CASE		).isalpha():
      a__			:      Tuple            =f'''Barcode \'{barcode}\' has alphabetic characters.'''
      raise ValueError(SCREAMING_SNAKE_CASE		)
    elif int(SCREAMING_SNAKE_CASE		) < 0:
      raise ValueError("The entered barcode has a negative value. Try again."		)
    else:
      return int(SCREAMING_SNAKE_CASE		)
  
  
  if __name__ == "__main__":
       import doctest
  
       doctest.testmod()
       UpperCAmelCase			:			List[str]	  = get_barcode(input("""Barcode: """).strip())
  
       if is_valid(barcode):
            print(F"""'{barcode}' is a valid barcode.""")
       else:
            print(F"""'{barcode}' is NOT a valid barcode.""")
  
  
  
  
  
  
  