





"""simple docstring"""


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__       :  str       		=					logging.get_logger(__name__)

a__       :  int       		=					{'''vocab_file''': '''tokenizer.model'''}

a__       :  Optional[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__       :  Optional[int]       		=					{
    '''hf-internal-testing/llama-tokenizer''': 2_0_4_8,
}
a__       :  Optional[Any]       		=					'''▁'''

a__       :  Optional[Any]       		=					'''[INST]''', '''[/INST]'''
a__       :  Optional[Any]       		=					'''<<SYS>>\n''', '''\n<</SYS>>\n\n'''

# fmt: off
a__       :  int       		=					'''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_					(  snake_case__				):
       snake_case__					:				Dict									=  VOCAB_FILES_NAMES
       snake_case__					:				Any									=  PRETRAINED_VOCAB_FILES_MAP
       snake_case__					:				Optional[int]									=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       snake_case__					:				Optional[Any]									=  ['input_ids', 'attention_mask']

       def __init__(      self ,       __SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE="<unk>" ,       __SCREAMING_SNAKE_CASE="<s>" ,       __SCREAMING_SNAKE_CASE="</s>" ,       __SCREAMING_SNAKE_CASE=None ,       __SCREAMING_SNAKE_CASE = None ,       __SCREAMING_SNAKE_CASE=True ,       __SCREAMING_SNAKE_CASE=False ,       __SCREAMING_SNAKE_CASE=False ,       __SCREAMING_SNAKE_CASE=True ,       **__SCREAMING_SNAKE_CASE ,       ):






        '''simple docstring'''

        snake_case__     				=					{} if sp_model_kwargs is None else sp_model_kwargs
        snake_case__     				=					AddedToken(__lowerCAmelCase ,       lstrip=__lowerCAmelCase ,       rstrip=__lowerCAmelCase  ) if isinstance(__lowerCAmelCase ,       __lowerCAmelCase  ) else bos_token
        snake_case__     				=					AddedToken(__lowerCAmelCase ,       lstrip=__lowerCAmelCase ,       rstrip=__lowerCAmelCase  ) if isinstance(__lowerCAmelCase ,       __lowerCAmelCase  ) else eos_token
        snake_case__     				=					AddedToken(__lowerCAmelCase ,       lstrip=__lowerCAmelCase ,       rstrip=__lowerCAmelCase  ) if isinstance(__lowerCAmelCase ,       __lowerCAmelCase  ) else unk_token
        snake_case__     				=					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"  )
        snake_case__     				=					legacy
        snake_case__     				=					vocab_file
        snake_case__     				=					add_bos_token
        snake_case__     				=					add_eos_token
        snake_case__     				=					spm.SentencePieceProcessor(**self.sp_model_kwargs  )
        self.sp_model.Load(__lowerCAmelCase  )

       def __getstate__(      self  ):






        '''simple docstring'''

        snake_case__     				=					self.__dict__.copy()
        snake_case__     				=					None
        snake_case__     				=					self.sp_model.serialized_model_proto()
        return state

       def __setstate__(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        snake_case__     				=					d
        snake_case__     				=					spm.SentencePieceProcessor(**self.sp_model_kwargs  )
        self.sp_model.LoadFromSerializedProto(self.sp_model_proto  )

       @property
       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        return self.sp_model.get_piece_size()

       def 		_SCREAMING_SNAKE_CASE(      self  ):






        '''simple docstring'''

        snake_case__     				=					{self.convert_ids_to_tokens(__lowerCAmelCase  ): i for i in range(self.vocab_size  )}
        vocab.update(self.added_tokens_encoder  )
        return vocab

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE ,       **__SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        if not self.legacy:
         snake_case__     				=					SPIECE_UNDERLINE + text.replace(__lowerCAmelCase ,       " "  )
        return super().tokenize(__lowerCAmelCase ,       **__lowerCAmelCase  )

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        if not self.legacy:
         snake_case__     				=					text.startswith(__lowerCAmelCase  )
         if is_first:
          snake_case__     				=					text[1:]

        snake_case__     				=					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  ):
         snake_case__     				=					([tokens[0][1:]] if len(tokens[0]  ) > 1 else []) + tokens[1:]
        return tokens

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        return self.sp_model.piece_to_id(__lowerCAmelCase  )

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        snake_case__     				=					self.sp_model.IdToPiece(__lowerCAmelCase  )
        return token

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        snake_case__     				=					[]
        snake_case__     				=					""""""
        snake_case__     				=					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
          snake_case__     				=					True
          snake_case__     				=					[]
         else:
          current_sub_tokens.append(__lowerCAmelCase  )
          snake_case__     				=					False
        out_string += self.sp_model.decode(__lowerCAmelCase  )
        return out_string

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE = None  ):






        '''simple docstring'''

        if not os.path.isdir(__lowerCAmelCase  ):
         logger.error(F"Vocabulary path ({save_directory}) should be a directory"  )
         return
        snake_case__     				=					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:
          snake_case__     				=					self.sp_model.serialized_model_proto()
          fi.write(__lowerCAmelCase  )

        return (out_vocab_file,)

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE=None  ):






        '''simple docstring'''

        snake_case__     				=					[self.bos_token_id] if self.add_bos_token else []
        snake_case__     				=					[self.eos_token_id] if self.add_eos_token else []

        snake_case__     				=					bos_token_id + token_ids_a + eos_token_id

        if token_ids_a is not None:
         snake_case__     				=					output + bos_token_id + token_ids_a + eos_token_id

        return output

       def 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE = None ,       __SCREAMING_SNAKE_CASE = False  ):






        '''simple docstring'''

        if already_has_special_tokens:
         return super().get_special_tokens_mask(
             token_ids_a=__lowerCAmelCase ,       token_ids_a=__lowerCAmelCase ,       already_has_special_tokens=__lowerCAmelCase  )

        snake_case__     				=					[1] if self.add_bos_token else []
        snake_case__     				=					[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 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE ,       __SCREAMING_SNAKE_CASE = None  ):






        '''simple docstring'''

        snake_case__     				=					[self.bos_token_id] if self.add_bos_token else []
        snake_case__     				=					[self.eos_token_id] if self.add_eos_token else []

        snake_case__     				=					[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 		_SCREAMING_SNAKE_CASE(      self ,       __SCREAMING_SNAKE_CASE  ):






        '''simple docstring'''

        snake_case__     				=					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...)"  )

        snake_case__     				=					[]
        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]:
          snake_case__     				=					(
              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]:
         snake_case__     				=					(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'''





from __future__ import annotations

import random
import string




class      UpperCamelCase       :



  def __init__(			self		,     __lowerCAmelCase = None ):







      '''simple docstring'''


      _a				:							List[Any]							       =      passcode or self.__passcode_creator()
      _a				:							List[str]							       =      self.__make_key_list()
      _a				:							Optional[int]							       =      self.__make_shift_key()



  def __str__(			self ):







      '''simple docstring'''


      return "".join(self.__passcode )



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      for i in range(1		,     len(__lowerCAmelCase )		,     2 ):
          iterlist[i] *= -1
      return iterlist



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Optional[int]							       =      string.ascii_letters + string.digits
      _a				:							str							       =      [random.choice(__lowerCAmelCase ) for _ in range(random.randint(10		,     20 ) )]
      return password



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Dict							       =      (
          string.ascii_letters + string.digits + string.punctuation + """ \t\n"""
      )

      _a				:							str							       =      []

      # creates points known as breakpoints to break the key_list_options at those
      # points and pivot each substring
      _a				:							Dict							       =      sorted(set(self.__passcode ) )
      _a				:							list[str]							       =      []

      # algorithm for creating a new shuffled list, keys_l, out of key_list_options
      for i in key_list_options:
          temp_list.extend(__lowerCAmelCase )

          # checking breakpoints at which to pivot temporary sublist and add it into
          # keys_l
          if i in breakpoints or i == key_list_options[-1]:
              keys_l.extend(temp_list[::-1] )
              temp_list.clear()

        # returning a shuffled keys_l to prevent brute force guessing of shift key
      return keys_l



  def     a_							(			self ):







      '''simple docstring'''


      _a				:							Optional[Any]							       =      sum(self.__neg_pos([ord(__lowerCAmelCase ) for x in self.__passcode] ) )
      return num if num > 0 else len(self.__passcode )



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      _a				:							Tuple							       =      """"""

      # decoding shift like Caesar cipher algorithm implementing negative shift or
      # reverse shift or left shift
      for i in encoded_message:
          _a				:							List[str]							       =      self.__key_list.index(__lowerCAmelCase )
          decoded_message += self.__key_list[
              (position - self.__shift_key) % -len(self.__key_list )
          ]

      return decoded_message



  def     a_							(			self		,     __lowerCAmelCase ):







      '''simple docstring'''


      _a				:							List[str]							       =      """"""

      # encoding shift like Caesar cipher algorithm implementing positive shift or
      # forward shift or right shift
      for i in plaintext:
          _a				:							Any							       =      self.__key_list.index(__lowerCAmelCase )
          encoded_message += self.__key_list[
              (position + self.__shift_key) % len(self.__key_list )
          ]

      return encoded_message






def UpperCAmelCase    (       UpperCAmelCase_ = "Hello, this is a modified Caesar cipher"						):
    _a				:							Union[str, Any]							       =      ShuffledShiftCipher()
    return cipa.decrypt(cipa.encrypt(UpperCAmelCase_						)						)


if __name__ == "__main__":
  import doctest

  doctest.testmod()


