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:
 a_										=       None

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

a_						,      a_										=       "[INST]", "[/INST]"
a_						,      a_										=       "<<SYS>>\n", "\n<</SYS>>\n\n"

# fmt: off
a_										=       "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  (     _SCREAMING_SNAKE_CASE				):

      """simple docstring"""

      lowerCAmelCase__     :	Dict      =   VOCAB_FILES_NAMES
      lowerCAmelCase__     :	List[str]      =   LlamaTokenizer
      lowerCAmelCase__     :	Dict      =   "left"
      lowerCAmelCase__     :	List[str]      =   ["input_ids", "attention_mask"]







      def __init__(       self   :	Any	,    snake_case   :	Union[str, Any]=None	,    snake_case   :	List[str]=None	,    snake_case   :	Any=False	,    snake_case   :	str="<unk>"	,    snake_case   :	Union[str, Any]="<s>"	,    snake_case   :	List[Any]="</s>"	,    snake_case   :	str=True	,    snake_case   :	int=False	,    **snake_case   :	Optional[Any]	,    ):
          super().__init__(
              vocab_file=snake_case	,    tokenizer_file=snake_case	,    clean_up_tokenization_spaces=snake_case	,    unk_token=snake_case	,    bos_token=snake_case	,    eos_token=snake_case	,    **snake_case	,    )
          __UpperCamelCase											=  add_bos_token
          __UpperCamelCase											=  add_eos_token
          self.update_post_processor()

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







      def  snake_case		(       self   :	Any			):
          __UpperCamelCase											=  self.bos_token
          __UpperCamelCase											=  self.bos_token_id

          __UpperCamelCase											=  self.eos_token
          __UpperCamelCase											=  self.eos_token_id

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

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







      @property
      def  snake_case		(       self   :	Dict			):
          return self._add_eos_token







      @property
      def  snake_case		(       self   :	Optional[int]			):
          return self._add_bos_token







      @add_eos_token.setter
      def  snake_case		(       self   :	Any	,    snake_case   :	Union[str, Any]			):
          __UpperCamelCase											=  value
          self.update_post_processor()







      @add_bos_token.setter
      def  snake_case		(       self   :	int	,    snake_case   :	str			):
          __UpperCamelCase											=  value
          self.update_post_processor()







      def  snake_case		(       self   :	str	,    snake_case   :	str	,    snake_case   :	Optional[str] = None			):
          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(snake_case			):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory"			)
              return
          __UpperCamelCase											=  os.path.join(
              snake_case	,    (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)

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

          return (out_vocab_file,)







      def  snake_case		(       self   :	Tuple	,    snake_case   :	"Conversation"			):
          __UpperCamelCase											=  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...)'''			)

          __UpperCamelCase											=  []
          if len(conversation.past_user_inputs			) > 0:
              if not conversation.past_user_inputs[0].startswith(snake_case			) or E_SYS not in conversation.past_user_inputs[0]:
                  __UpperCamelCase											=  (
                      B_SYS + DEFAULT_SYSTEM_PROMPT + E_SYS + conversation.past_user_inputs[0]
                  )
          elif not dialogue[0][1].startswith(snake_case			) or E_SYS not in dialogue[0][1]:
              __UpperCamelCase											=  (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=snake_case			)
                  + [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=snake_case			)
          return dialog_tokens












def    __SCREAMING_SNAKE_CASE				(					lowercase_ )    ->		list:

    """simple docstring"""


    __UpperCamelCase											=  len(lowercase_ )

    # Set the gap value to be decreased by a factor of 1.3
    # after each iteration
    __UpperCamelCase											=  1.3

    # Continue sorting until the gap is 1
    while gap > 1:
        # Decrease the gap value
        __UpperCamelCase											=  int(gap / shrink )

        # Sort the elements using insertion sort
        for i in range(lowercase_   ,       len(lowercase_ ) ):
            __UpperCamelCase											=  collection[i]
            __UpperCamelCase											=  i
            while j >= gap and collection[j - gap] > temp:
                __UpperCamelCase											=  collection[j - gap]
                j -= gap
            __UpperCamelCase											=  temp

    return collection


if __name__ == "__main__":
 import doctest

 doctest.testmod()






