





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













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.""")






