code: 
  
  
  '''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:
      lowerCAmelCase__   	=				None
  
  lowerCAmelCase__   	=				logging.get_logger(__name__)
  lowerCAmelCase__   	=				{'vocab_file': 'tokenizer.model', 'tokenizer_file': 'tokenizer.json'}
  
  lowerCAmelCase__   	=				'[INST]', '[/INST]'
  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\\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   lowerCAmelCase__ (       lowercase_):
  
  
  
  
       '''simple docstring'''
       __SCREAMING_SNAKE_CASE						    =				VOCAB_FILES_NAMES
       __SCREAMING_SNAKE_CASE						    =				LlamaTokenizer
       __SCREAMING_SNAKE_CASE						    =				"""left"""
       __SCREAMING_SNAKE_CASE						    =				["""input_ids""", """attention_mask"""]
  
  
       def __init__(		self				,		__lowerCamelCase=None				,		__lowerCamelCase=None				,		__lowerCamelCase=False				,		__lowerCamelCase="<unk>"				,		__lowerCamelCase="<s>"				,		__lowerCamelCase="</s>"				,		__lowerCamelCase=True				,		__lowerCamelCase=False				,		**__lowerCamelCase				,		)    ->       Union[str, Any]:
              super().__init__(
                  vocab_file=__lowerCamelCase				,		tokenizer_file=__lowerCamelCase				,		clean_up_tokenization_spaces=__lowerCamelCase				,		unk_token=__lowerCamelCase				,		bos_token=__lowerCamelCase				,		eos_token=__lowerCamelCase				,		**__lowerCamelCase				,		)
              _A   : Optional[int]       					=				add_bos_token
              _A   : str       					=				add_eos_token
              self.update_post_processor()
  
              _A   : Tuple       					=				vocab_file
              _A   : List[str]       					=				False if not self.vocab_file else True
  
  
       def 				_lowerCamelCase				(		self)    ->       Any:
              _A   : Tuple       					=				self.bos_token
              _A   : int       					=				self.bos_token_id
  
              _A   : Optional[int]       					=				self.eos_token
              _A   : Any       					=				self.eos_token_id
  
              _A   : Union[str, Any]       					=				F"{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"
              _A   : Any       					=				F"{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"
  
              _A   : Optional[Any]       					=				[]
              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   : List[str]       					=				processors.TemplateProcessing(
                  single=__lowerCamelCase				,		pair=__lowerCamelCase				,		special_tokens=__lowerCamelCase)
  
  
       @property
       def 				_lowerCamelCase				(		self)    ->       List[str]:
              return self._add_eos_token
  
  
       @property
       def 				_lowerCamelCase				(		self)    ->       Any:
              return self._add_bos_token
  
  
       @add_eos_token.setter
       def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Union[str, Any]:
              _A   : Dict       					=				value
              self.update_post_processor()
  
  
       @add_bos_token.setter
       def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Any:
              _A   : Any       					=				value
              self.update_post_processor()
  
  
       def 				_lowerCamelCase				(		self				,		__lowerCamelCase				,		__lowerCamelCase = None)    ->       Tuple:
  
  
  
  
  
  
  
              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(__lowerCamelCase):
                     logger.error(F"Vocabulary path ({save_directory}) should be a directory")
                     return
              _A   : List[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):
                     copyfile(self.vocab_file				,		__lowerCamelCase)
  
              return (out_vocab_file,)
  
  
       def 				_lowerCamelCase				(		self				,		__lowerCamelCase)    ->       Union[str, Any]:
              _A   : Optional[Any]       					=				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   : str       					=				[]
              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   : List[str]       					=				(
                                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   : int       					=				(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: 
  
  
  lowerCAmelCase__   	=				'\n# Transformers installation\n! pip install transformers datasets evaluate\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
  
  lowerCAmelCase__   	=				[{'type': 'code', 'content': INSTALL_CONTENT}]
  lowerCAmelCase__   	=				{
      '{processor_class}': 'FakeProcessorClass',
      '{model_class}': 'FakeModelClass',
      '{object_class}': 'FakeObjectClass',
  }
  