


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_       :Any				  =				None

a_       :Dict				  =				logging.get_logger(__name__)
a_       :Optional[int]				  =				{"vocab_file": "tokenizer.model", "tokenizer_file": "tokenizer.json"}

a_       :List[str]				  =				"[INST]", "[/INST]"
a_       :Optional[Any]				  =				"<<SYS>>\n", "\n<</SYS>>\n\n"

# fmt: off
a_       :Tuple				  =				"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"""


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






     def __init__(	self  :  Union[str, Any],			_snake_case  :  Tuple=None,			_snake_case  :  Optional[Any]=None,			_snake_case  :  Any=False,			_snake_case  :  Union[str, Any]="<unk>",			_snake_case  :  Optional[Any]="<s>",			_snake_case  :  Tuple="</s>",			_snake_case  :  int=True,			_snake_case  :  Any=False,			**_snake_case  :  Tuple,			)       ->int:
            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,			)
            snake_case__							:     Union[str, Any]            =     add_bos_token
            snake_case__							:     int            =     add_eos_token
            self.update_post_processor()

            snake_case__							:     Dict            =     vocab_file
            snake_case__							:     Any            =     False if not self.vocab_file else True






     def        lowercase_       (	self  :  Tuple )       ->Dict:
            snake_case__							:     List[str]            =     self.bos_token
            snake_case__							:     str            =     self.bos_token_id

            snake_case__							:     Optional[Any]            =     self.eos_token
            snake_case__							:     Optional[Any]            =     self.eos_token_id

            snake_case__							:     int            =     F'''{(bos+":0 ") * self.add_bos_token}$A:0{(" "+eos+":0") * self.add_eos_token}'''
            snake_case__							:     List[Any]            =     F'''{single}{(" "+bos+":1") * self.add_bos_token} $B:1{(" "+eos+":1") * self.add_eos_token}'''

            snake_case__							:     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) )
            snake_case__							:     Optional[int]            =     processors.TemplateProcessing(
                single=_snake_case,			pair=_snake_case,			special_tokens=_snake_case )






     @property
     def        lowercase_       (	self  :  Dict )       ->Tuple:
            return self._add_eos_token






     @property
     def        lowercase_       (	self  :  Tuple )       ->Union[str, Any]:
            return self._add_bos_token






     @add_eos_token.setter
     def        lowercase_       (	self  :  Optional[Any],			_snake_case  :  Optional[int] )       ->Optional[Any]:
            snake_case__							:     Tuple            =     value
            self.update_post_processor()






     @add_bos_token.setter
     def        lowercase_       (	self  :  Optional[Any],			_snake_case  :  Optional[int] )       ->str:
            snake_case__							:     Optional[Any]            =     value
            self.update_post_processor()






     def        lowercase_       (	self  :  List[Any],			_snake_case  :  str,			_snake_case  :  Optional[str] = None )       ->Tuple[str]:
            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
            snake_case__							:     Any            =     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        lowercase_       (	self  :  Optional[Any],			_snake_case  :  "Conversation" )       ->int:
            snake_case__							:     Dict            =     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__							:     Tuple            =     []
            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]:
                          snake_case__							:     List[Any]            =     (
                              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]:
                   snake_case__							:     Optional[Any]            =     (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 	lowercase_							(A			:			Dict				):
       snake_case__							:     Optional[int]            =     len(A				)
       for i in range(length - 1				):
              snake_case__							:     List[str]            =     False
              for j in range(length - 1 - i				):
                     if collection[j] > collection[j + 1]:
                            snake_case__							:     Optional[Any]            =     True
                            snake_case__     ,    snake_case__							:     Dict            =     collection[j + 1], collection[j]
              if not swapped:
                     break  # Stop iteration if the collection is sorted.
       return collection


if __name__ == "__main__":
 import doctest
 import time

 doctest.testmod()

 a_       :Any				  =				input("Enter numbers separated by a comma:").strip()
 a_       :Optional[Any]				  =				[int(item) for item in user_input.split(",")]
 a_       :Optional[int]				  =				time.process_time()
 print(*bubble_sort(unsorted), sep=",")
 print(F"""Processing time: {(time.process_time() - start)%1e9 + 7}""")






