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
  
  a     :			Dict					    =						logging.get_logger(__name__)
  
  a     :			Optional[int]					    =						{"""vocab_file""": """tokenizer.model"""}
  
  a     :			Union[str, Any]					    =						{
      """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""",
      },
  }
  a     :			str					    =						{
      """hf-internal-testing/llama-tokenizer""": 2_0_4_8,
  }
  a     :			Any					    =						"""▁"""
  
  a    ,   a     :			List[str]					    =						"""[INST]""", """[/INST]"""
  a    ,   a     :			Tuple					    =						"""<<SYS>>\n""", """\n<</SYS>>\n\n"""
  
  # fmt: off
  a     :			Dict					    =						"""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 				_lowercase						(    UpperCAmelCase__ ):
  
  
  
  
  
  
      '''simple docstring'''
      SCREAMING_SNAKE_CASE:							Dict        =						VOCAB_FILES_NAMES
      SCREAMING_SNAKE_CASE:							str        =						PRETRAINED_VOCAB_FILES_MAP
      SCREAMING_SNAKE_CASE:							Optional[int]        =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      SCREAMING_SNAKE_CASE:							List[str]        =						['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__					,	):
         lowerCAmelCase_:       List[str]         =  {} if sp_model_kwargs is None else sp_model_kwargs
         lowerCAmelCase_:       int         =  AddedToken(lowerCamelCase__					,	lstrip=lowerCamelCase__					,	rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__					,	lowerCamelCase__   ) else bos_token
         lowerCAmelCase_:       Any         =  AddedToken(lowerCamelCase__					,	lstrip=lowerCamelCase__					,	rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__					,	lowerCamelCase__   ) else eos_token
         lowerCAmelCase_:       Any         =  AddedToken(lowerCamelCase__					,	lstrip=lowerCamelCase__					,	rstrip=lowerCamelCase__   ) if isinstance(lowerCamelCase__					,	lowerCamelCase__   ) else unk_token
         lowerCAmelCase_:       Any         =  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"   )
         lowerCAmelCase_:       List[str]         =  legacy
         lowerCAmelCase_:       Any         =  vocab_file
         lowerCAmelCase_:       Union[str, Any]         =  add_bos_token
         lowerCAmelCase_:       List[str]         =  add_eos_token
         lowerCAmelCase_:       List[str]         =  spm.SentencePieceProcessor(**self.sp_model_kwargs   )
         self.sp_model.Load(lowerCamelCase__   )
  
  
  
  
      def __getstate__(						self   ):
         lowerCAmelCase_:       int         =  self.__dict__.copy()
         lowerCAmelCase_:       int         =  None
         lowerCAmelCase_:       Any         =  self.sp_model.serialized_model_proto()
         return state
  
  
  
  
      def __setstate__(						self					,	lowerCamelCase__   ):
         lowerCAmelCase_:       Tuple         =  d
         lowerCAmelCase_:       Tuple         =  spm.SentencePieceProcessor(**self.sp_model_kwargs   )
         self.sp_model.LoadFromSerializedProto(self.sp_model_proto   )
  
  
  
  
      @property
      def     _a						(						self   ):
         return self.sp_model.get_piece_size()
  
  
  
  
      def     _a						(						self   ):
         lowerCAmelCase_:       Dict         =  {self.convert_ids_to_tokens(lowerCamelCase__   ): i for i in range(self.vocab_size   )}
         vocab.update(self.added_tokens_encoder   )
         return vocab
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__					,	**lowerCamelCase__   ):
         # Replace the SPIECE_UNDERLINE with a space to make sure SPIECE_UNDERLINE is only used at
         # the beginning of the text
         if not self.legacy:
            lowerCAmelCase_:       str         =  SPIECE_UNDERLINE + text.replace(lowerCamelCase__					,	" "   )
         return super().tokenize(lowerCamelCase__					,	**lowerCamelCase__   )
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__   ):
         if not self.legacy:
            lowerCAmelCase_:       Optional[int]         =  text.startswith(lowerCamelCase__   )
            if is_first:
               lowerCAmelCase_:       Union[str, Any]         =  text[1:]
  
         lowerCAmelCase_:       Optional[int]         =  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__   ):
            lowerCAmelCase_:       Any         =  ([tokens[0][1:]] if len(tokens[0]   ) > 1 else []) + tokens[1:]
         return tokens
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__   ):
         return self.sp_model.piece_to_id(lowerCamelCase__   )
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__   ):
         lowerCAmelCase_:       Optional[Any]         =  self.sp_model.IdToPiece(lowerCamelCase__   )
         return token
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__   ):
         lowerCAmelCase_:       Optional[Any]         =  []
         lowerCAmelCase_:       List[str]         =  ""
         lowerCAmelCase_:       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
               lowerCAmelCase_:       Dict         =  True
               lowerCAmelCase_:       str         =  []
            else:
               current_sub_tokens.append(lowerCamelCase__   )
               lowerCAmelCase_:       Tuple         =  False
         out_string += self.sp_model.decode(lowerCamelCase__   )
         return out_string
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__					,	lowerCamelCase__ = None   ):
         if not os.path.isdir(lowerCamelCase__   ):
            logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''   )
            return
         lowerCAmelCase_:       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:
               lowerCAmelCase_:       List[Any]         =  self.sp_model.serialized_model_proto()
               fi.write(lowerCamelCase__   )
  
         return (out_vocab_file,)
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__					,	lowerCamelCase__=None   ):
         lowerCAmelCase_:       Any         =  [self.bos_token_id] if self.add_bos_token else []
         lowerCAmelCase_:       Optional[int]         =  [self.eos_token_id] if self.add_eos_token else []
  
         lowerCAmelCase_:       Union[str, Any]         =  bos_token_id + token_ids_a + eos_token_id
  
         if token_ids_a is not None:
            lowerCAmelCase_:       Optional[Any]         =  output + bos_token_id + token_ids_a + eos_token_id
  
         return output
  
  
  
  
      def     _a						(						self					,	lowerCamelCase__					,	lowerCamelCase__ = None					,	lowerCamelCase__ = False   ):
         if already_has_special_tokens:
            return super().get_special_tokens_mask(
                token_ids_a=lowerCamelCase__					,	token_ids_a=lowerCamelCase__					,	already_has_special_tokens=lowerCamelCase__   )
  
         lowerCAmelCase_:       List[str]         =  [1] if self.add_bos_token else []
         lowerCAmelCase_:       str         =  [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     _a						(						self					,	lowerCamelCase__					,	lowerCamelCase__ = None   ):
         lowerCAmelCase_:       Dict         =  [self.bos_token_id] if self.add_bos_token else []
         lowerCAmelCase_:       Optional[int]         =  [self.eos_token_id] if self.add_eos_token else []
  
         lowerCAmelCase_:       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     _a						(						self					,	lowerCamelCase__   ):
         lowerCAmelCase_:       int         =  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...)"   )
  
         lowerCAmelCase_:       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]:
               lowerCAmelCase_:       Tuple         =  (
                   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]:
            lowerCAmelCase_:       List[str]         =  (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: from .balanced_parentheses import balanced_parentheses
  from .stack import Stack
  def 		snake_case__  (		lowercase				):
     return {"+": 1, "-": 1, "*": 2, "/": 2, "^": 3}.get(lowercase       ,							-1				)
  def 		snake_case__  (		lowercase				):
     if not balanced_parentheses(lowercase				):
        raise ValueError("Mismatched parentheses"				)
     lowerCAmelCase_:       Stack[str]         =  Stack()
     lowerCAmelCase_:       Union[str, Any]         =  []
     for char in expression_str:
        if char.isalpha() or char.isdigit():
           postfix.append(lowercase				)
        elif char == "(":
           stack.push(lowercase				)
        elif char == ")":
           while not stack.is_empty() and stack.peek() != "(":
              postfix.append(stack.pop()				)
           stack.pop()
        else:
           while not stack.is_empty() and precedence(lowercase				) <= precedence(stack.peek()				):
              postfix.append(stack.pop()				)
           stack.push(lowercase				)
     while not stack.is_empty():
        postfix.append(stack.pop()				)
     return " ".join(lowercase				)
  
  
  if __name__ == "__main__":
   from doctest import testmod
  
   testmod()
   a     :			int					    =						"""a+b*(c^d-e)^(f+g*h)-i"""
  
   print("""Infix to Postfix Notation demonstration:\n""")
   print("""Infix notation: """ + expression)
   print("""Postfix notation: """ + infix_to_postfix(expression))