'''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:
 snake_case  =			None

snake_case  =			logging.get_logger(__name__)
snake_case  =			{'''vocab_file''': '''tokenizer.model''', '''tokenizer_file''': '''tokenizer.json'''}

snake_case,     snake_case  =			'''[INST]''', '''[/INST]'''
snake_case,     snake_case  =			'''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
snake_case  =			'''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        SCREAMING_SNAKE_CASE   (				__a ):
  """simple docstring"""







  __A     =		VOCAB_FILES_NAMES
  __A     =		LlamaTokenizer
  __A     =		"left"
  __A     =		["input_ids", "attention_mask"]



  def __init__(  self   :					List[str]					,					__lowerCAmelCase   :					List[str]=None					,					__lowerCAmelCase   :					Optional[int]=None					,					__lowerCAmelCase   :					Dict=False					,					__lowerCAmelCase   :					Optional[int]="<unk>"					,					__lowerCAmelCase   :					List[Any]="<s>"					,					__lowerCAmelCase   :					List[str]="</s>"					,					__lowerCAmelCase   :					str=True					,					__lowerCAmelCase   :					Any=False					,					**__lowerCAmelCase   :					int					,					):


        """simple docstring"""



        super().__init__(
            vocab_file=__lowerCAmelCase					,					tokenizer_file=__lowerCAmelCase					,					clean_up_tokenization_spaces=__lowerCAmelCase					,					unk_token=__lowerCAmelCase					,					bos_token=__lowerCAmelCase					,					eos_token=__lowerCAmelCase					,					**__lowerCAmelCase					,					)
        _lowerCAmelCase		   =   add_bos_token
        _lowerCAmelCase		   =   add_eos_token
        self.update_post_processor()

        _lowerCAmelCase		   =   vocab_file
        _lowerCAmelCase		   =   False if not self.vocab_file else True



  def   a   (  self   :					Union[str, Any]					):


        """simple docstring"""



        _lowerCAmelCase		   =   self.bos_token
        _lowerCAmelCase		   =   self.bos_token_id

        _lowerCAmelCase		   =   self.eos_token
        _lowerCAmelCase		   =   self.eos_token_id

        _lowerCAmelCase		   =   F"{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"
        _lowerCAmelCase		   =   F"{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"

        _lowerCAmelCase		   =   []
        if self.add_bos_token:
              special_tokens.append((bos, bos_token_id)					)
        if self.add_eos_token:
              special_tokens.append((eos, eos_token_id)					)
        _lowerCAmelCase		   =   processors.TemplateProcessing(
            single=__lowerCAmelCase					,					pair=__lowerCAmelCase					,					special_tokens=__lowerCAmelCase					)



  @property
  def   a   (  self   :					Optional[int]					):


        """simple docstring"""



        return self._add_eos_token



  @property
  def   a   (  self   :					Dict					):


        """simple docstring"""



        return self._add_bos_token



  @add_eos_token.setter
  def   a   (  self   :					Optional[Any]					,					__lowerCAmelCase   :					List[Any]					):


        """simple docstring"""



        _lowerCAmelCase		   =   value
        self.update_post_processor()



  @add_bos_token.setter
  def   a   (  self   :					Union[str, Any]					,					__lowerCAmelCase   :					Tuple					):


        """simple docstring"""



        _lowerCAmelCase		   =   value
        self.update_post_processor()



  def   a   (  self   :					str					,					__lowerCAmelCase   :					str					,					__lowerCAmelCase   :					Optional[str] = None					):


        """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(__lowerCAmelCase					):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory"					)
              return
        _lowerCAmelCase		   =   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   a   (  self   :					Dict					,					__lowerCAmelCase   :					"Conversation"					):


        """simple docstring"""



        _lowerCAmelCase		   =   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		   =   []
        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		   =   (
                        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		   =   (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






'''simple docstring'''




snake_case  =			{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

snake_case  =			{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}







def 			A_   ( _lowerCamelCase			:							dict  ,  _lowerCamelCase			:							int  ,  _lowerCamelCase			:							list    ):
      _lowerCAmelCase		   =   True
      _lowerCAmelCase		   =   []

      for neighbour in graph[vert]:
            if not visited[neighbour]:
                  connected_verts += dfs(_lowerCamelCase  ,  _lowerCamelCase  ,  _lowerCamelCase    )

      return [vert, *connected_verts]







def 			A_   ( _lowerCamelCase			:							dict    ):
      _lowerCAmelCase		   =   len(_lowerCamelCase    )
      _lowerCAmelCase		   =   graph_size * [False]
      _lowerCAmelCase		   =   []

      for i in range(_lowerCamelCase    ):
            if not visited[i]:
                  _lowerCAmelCase		   =   dfs(_lowerCamelCase  ,  _lowerCamelCase  ,  _lowerCamelCase    )
                  components_list.append(_lowerCamelCase    )

      return components_list


if __name__ == "__main__":
 import doctest

 doctest.testmod()





