

"""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:
 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\
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        _UpperCamelCase	(						lowerCamelCase__	):


  """simple docstring"""





  snake_case_        =    VOCAB_FILES_NAMES
  snake_case_        =    LlamaTokenizer
  snake_case_        =    'left'
  snake_case_        =    ['input_ids', 'attention_mask']



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


         '''simple docstring'''





         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       ,       )
         __magic_name__			:		Tuple        =     add_bos_token
         __magic_name__			:		Dict        =     add_eos_token
         self.update_post_processor()

         __magic_name__			:		str        =     vocab_file
         __magic_name__			:		List[Any]        =     False if not self.vocab_file else True



  def 							_UpperCAmelCase      ( self					: Optional[int]      )	->			Tuple:


         '''simple docstring'''





         __magic_name__			:		Union[str, Any]        =     self.bos_token
         __magic_name__			:		List[str]        =     self.bos_token_id

         __magic_name__			:		Union[str, Any]        =     self.eos_token
         __magic_name__			:		Optional[Any]        =     self.eos_token_id

         __magic_name__			:		str        =     f"""{(bos+':0 ') * self.add_bos_token}$A:0{(' '+eos+':0') * self.add_eos_token}"""
         __magic_name__			:		List[str]        =     f"""{single}{(' '+bos+':1') * self.add_bos_token} $B:1{(' '+eos+':1') * self.add_eos_token}"""

         __magic_name__			:		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)      )
         __magic_name__			:		str        =     processors.TemplateProcessing(
             single=snake_case       ,       pair=snake_case       ,       special_tokens=snake_case      )



  @property
  def 							_UpperCAmelCase      ( self					: List[str]      )	->			Any:


         '''simple docstring'''





         return self._add_eos_token



  @property
  def 							_UpperCAmelCase      ( self					: Tuple      )	->			Optional[Any]:


         '''simple docstring'''





         return self._add_bos_token



  @add_eos_token.setter
  def 							_UpperCAmelCase      ( self					: Tuple       ,       snake_case					: Optional[int]      )	->			List[Any]:


         '''simple docstring'''





         __magic_name__			:		List[Any]        =     value
         self.update_post_processor()



  @add_bos_token.setter
  def 							_UpperCAmelCase      ( self					: Optional[int]       ,       snake_case					: Optional[Any]      )	->			Union[str, Any]:


         '''simple docstring'''





         __magic_name__			:		Tuple        =     value
         self.update_post_processor()



  def 							_UpperCAmelCase      ( self					: Tuple       ,       snake_case					: str       ,       snake_case					: Optional[str] = None      )	->			Tuple[str]:


         '''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(snake_case      ):
                logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""      )
                return
         __magic_name__			:		int        =     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 							_UpperCAmelCase      ( self					: int       ,       snake_case					: "Conversation"      )	->			Union[str, Any]:


         '''simple docstring'''





         __magic_name__			:		List[Any]        =     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...)'''      )

         __magic_name__			:		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]:
                       __magic_name__			:		Optional[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]:
                __magic_name__			:		List[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



"""simple docstring"""
from collections import defaultdict







def       UpperCamelCase_					(     lowerCamelCase							:					str   )						->     dict:



       """simple docstring"""







       __magic_name__			:		defaultdict[str, int]        =     defaultdict(lowerCamelCase   )
       # Creating a dictionary containing count of each word
       for word in sentence.split():
              occurrence[word] += 1
       return occurrence


if __name__ == "__main__":
 for word, count in word_occurrence("""INPUT STRING""").items():
  print(F"""{word}: {count}""")
