






"""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:
       lowercase_    					=					None

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

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

# fmt: off
lowercase_    					=					'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  snake_case		(							__lowerCamelCase						):


   '''simple docstring'''

   A_						:     Dict									=			VOCAB_FILES_NAMES
   A_						:     Tuple									=			LlamaTokenizer
   A_						:     int									=			"left"
   A_						:     List[Any]									=			["input_ids", "attention_mask"]


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

     '''simple docstring'''
     super().__init__(
         vocab_file=_UpperCamelCase,	tokenizer_file=_UpperCamelCase,	clean_up_tokenization_spaces=_UpperCamelCase,	unk_token=_UpperCamelCase,	bos_token=_UpperCamelCase,	eos_token=_UpperCamelCase,	**_UpperCamelCase,	)
     __A						      =			add_bos_token
     __A						      =			add_eos_token
     self.update_post_processor()

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


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

     '''simple docstring'''
     __A						      =			self.bos_token
     __A						      =			self.bos_token_id

     __A						      =			self.eos_token
     __A						      =			self.eos_token_id

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

     __A						      =			[]
     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						      =			processors.TemplateProcessing(
         single=_UpperCamelCase,	pair=_UpperCamelCase,	special_tokens=_UpperCamelCase  )


   @property
   def     _SCREAMING_SNAKE_CASE    (     self			:					Optional[Any]  ):

     '''simple docstring'''
     return self._add_eos_token


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

     '''simple docstring'''
     return self._add_bos_token


   @add_eos_token.setter
   def     _SCREAMING_SNAKE_CASE    (     self			:					List[str],	_lowerCamelCase			:					Optional[Any]  ):

     '''simple docstring'''
     __A						      =			value
     self.update_post_processor()


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

     '''simple docstring'''
     __A						      =			value
     self.update_post_processor()


   def     _SCREAMING_SNAKE_CASE    (     self			:					Optional[Any],	_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(_UpperCamelCase  ):
       logger.error(f'Vocabulary path ({save_directory}) should be a directory'  )
       return
     __A						      =			os.path.join(
         _UpperCamelCase,	(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )

     if os.path.abspath(self.vocab_file  ) != os.path.abspath(_UpperCamelCase  ):
       copyfile(self.vocab_file,	_UpperCamelCase  )

     return (out_vocab_file,)






   def     _SCREAMING_SNAKE_CASE    (     self			:					Optional[Any],	_lowerCamelCase			:					"Conversation"  ):

     '''simple docstring'''
     __A						      =			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						      =			[]
     if len(conversation.past_user_inputs  ) > 0:
       if not conversation.past_user_inputs[0].startswith(_UpperCamelCase  ) or E_SYS not in conversation.past_user_inputs[0]:
         __A						      =			(
             B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
         )
     elif not dialogue[0][1].startswith(_UpperCamelCase  ) or E_SYS not in dialogue[0][1]:
       __A						      =			(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=_UpperCamelCase  )
             + [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=_UpperCamelCase  )
     return dialog_tokens












"""simple docstring"""


def  lowerCAmelCase    (   __UpperCamelCase			):




  """simple docstring"""







  if not isinstance(__UpperCamelCase		,	__UpperCamelCase			):
    raise ValueError('''Input series is not valid, valid series - [2, 4, 8]'''			)
  if len(__UpperCamelCase			) == 0:
    raise ValueError('''Input list must be a non empty list'''			)
  if len(__UpperCamelCase			) == 1:
    return True
  try:
    __A						      =			series[1] / series[0]
    for index in range(len(__UpperCamelCase			) - 1			):
      if series[index + 1] / series[index] != common_ratio:
        return False
  except ZeroDivisionError:
    return False
  return True



def  lowerCAmelCase    (   __UpperCamelCase			):




  """simple docstring"""







  if not isinstance(__UpperCamelCase		,	__UpperCamelCase			):
    raise ValueError('''Input series is not valid, valid series - [2, 4, 8]'''			)
  if len(__UpperCamelCase			) == 0:
    raise ValueError('''Input list must be a non empty list'''			)
  __A						      =			1
  for value in series:
    answer *= value
  return pow(__UpperCamelCase		,	1 / len(__UpperCamelCase			)			)


if __name__ == "__main__":
       import doctest

       doctest.testmod()




