






import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


if TYPE_CHECKING:
 from transformers.pipelines.conversational import Conversation

lowerCamelCase     :							Union[str, Any]    =logging.get_logger(__name__)


lowerCamelCase     :							List[Any]    ={
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
}

lowerCamelCase     :							Union[str, Any]    ={
    '''vocab_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/vocab.json'''},
    '''merges_file''': {'''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/merges.txt'''},
    '''tokenizer_config_file''': {
        '''facebook/blenderbot-3B''': '''https://huggingface.co/facebook/blenderbot-3B/resolve/main/tokenizer_config.json'''
    },
}

lowerCamelCase     :							str    ={'''facebook/blenderbot-3B''': 128}







@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 		SCREAMING_SNAKE_CASE							( )			->     Optional[int]:
     UpperCamelCase__      :       List[str]	    =  (
         list(range(ord("!"      ) ,   ord("~"      ) + 1      )      ) + list(range(ord("¡"      ) ,   ord("¬"      ) + 1      )      ) + list(range(ord("®"      ) ,   ord("ÿ"      ) + 1      )      )
     )
     UpperCamelCase__      :       List[Any]	    =  bs[:]
     UpperCamelCase__      :       List[Any]	    =  0
     for b in range(2**8      ):
          if b not in bs:
               bs.append(__lowerCAmelCase      )
               cs.append(2**8 + n      )
               n += 1
     UpperCamelCase__      :       Optional[int]	    =  [chr(__lowerCAmelCase      ) for n in cs]
     return dict(zip(__lowerCAmelCase ,   __lowerCAmelCase      )      )







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase      )			->     Optional[Any]:
     UpperCamelCase__      :       List[str]	    =  set()
     UpperCamelCase__      :       Union[str, Any]	    =  word[0]
     for char in word[1:]:
          pairs.add((prev_char, char)      )
          UpperCamelCase__      :       int	    =  char
     return pairs





class       __a  (   A__	):
 _lowerCAmelCase	:	List[str]				=			VOCAB_FILES_NAMES
 _lowerCAmelCase	:	List[str]				=			PRETRAINED_VOCAB_FILES_MAP
 _lowerCAmelCase	:	Dict				=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowerCAmelCase	:	Optional[int]				=			['''input_ids''', '''attention_mask''']







 def __init__(		self :       Any							,       SCREAMING_SNAKE_CASE :       Dict							,       SCREAMING_SNAKE_CASE :       List[Any]							,       SCREAMING_SNAKE_CASE :       Union[str, Any]="replace"							,       SCREAMING_SNAKE_CASE :       Any="<s>"							,       SCREAMING_SNAKE_CASE :       List[Any]="</s>"							,       SCREAMING_SNAKE_CASE :       List[str]="</s>"							,       SCREAMING_SNAKE_CASE :       Optional[Any]="<s>"							,       SCREAMING_SNAKE_CASE :       Any="<unk>"							,       SCREAMING_SNAKE_CASE :       List[str]="<pad>"							,       SCREAMING_SNAKE_CASE :       List[Any]="<mask>"							,       SCREAMING_SNAKE_CASE :       Optional[Any]=False							,       **SCREAMING_SNAKE_CASE :       Tuple							,       ):


      '''simple docstring'''






      UpperCamelCase__      :       str	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else bos_token
      UpperCamelCase__      :       Any	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else eos_token
      UpperCamelCase__      :       Union[str, Any]	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else sep_token
      UpperCamelCase__      :       Union[str, Any]	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else cls_token
      UpperCamelCase__      :       List[str]	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else unk_token
      UpperCamelCase__      :       str	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else pad_token

      # Mask token behave like a normal word, i.e. include the space before it
      UpperCamelCase__      :       Union[str, Any]	    =  AddedToken(SCREAMING_SNAKE_CASE							,       lstrip=SCREAMING_SNAKE_CASE							,       rstrip=SCREAMING_SNAKE_CASE						) if isinstance(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						) else mask_token

      super().__init__(
          errors=SCREAMING_SNAKE_CASE							,       bos_token=SCREAMING_SNAKE_CASE							,       eos_token=SCREAMING_SNAKE_CASE							,       unk_token=SCREAMING_SNAKE_CASE							,       sep_token=SCREAMING_SNAKE_CASE							,       cls_token=SCREAMING_SNAKE_CASE							,       pad_token=SCREAMING_SNAKE_CASE							,       mask_token=SCREAMING_SNAKE_CASE							,       add_prefix_space=SCREAMING_SNAKE_CASE							,       **SCREAMING_SNAKE_CASE							,       )

      with open(SCREAMING_SNAKE_CASE							,       encoding="utf-8"						) as vocab_handle:
           UpperCamelCase__      :       List[str]	    =  json.load(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       str	    =  {v: k for k, v in self.encoder.items()}
      UpperCamelCase__      :       List[Any]	    =  errors  # how to handle errors in decoding
      UpperCamelCase__      :       str	    =  bytes_to_unicode()
      UpperCamelCase__      :       List[str]	    =  {v: k for k, v in self.byte_encoder.items()}
      with open(SCREAMING_SNAKE_CASE							,       encoding="utf-8"						) as merges_handle:
           UpperCamelCase__      :       str	    =  merges_handle.read().split("\n"						)[1:-1]
      UpperCamelCase__      :       Tuple	    =  [tuple(merge.split()						) for merge in bpe_merges]
      UpperCamelCase__      :       Any	    =  dict(zip(SCREAMING_SNAKE_CASE							,       range(len(SCREAMING_SNAKE_CASE						)						)						)						)
      UpperCamelCase__      :       Tuple	    =  {}
      UpperCamelCase__      :       Optional[Any]	    =  add_prefix_space

      # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
      UpperCamelCase__      :       Tuple	    =  re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"						)







 @property
 # Copied from transformers.models.roberta.tokenization_roberta.RobertaTokenizer.vocab_size with Roberta->Blenderbot, RoBERTa->Blenderbot
 def  __lowercase (		self :       int						):


      '''simple docstring'''






      return len(self.encoder						)







 def  __lowercase (		self :       List[str]						):


      '''simple docstring'''






      return dict(self.encoder							,       **self.added_tokens_encoder						)







 def  __lowercase (		self :       Tuple							,       SCREAMING_SNAKE_CASE :       Union[str, Any]						):


      '''simple docstring'''






      if token in self.cache:
           return self.cache[token]
      UpperCamelCase__      :       Optional[Any]	    =  tuple(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Optional[int]	    =  get_pairs(SCREAMING_SNAKE_CASE						)

      if not pairs:
           return token

      while True:
           UpperCamelCase__      :       str	    =  min(SCREAMING_SNAKE_CASE							,       key=lambda SCREAMING_SNAKE_CASE						: self.bpe_ranks.get(SCREAMING_SNAKE_CASE							,       float("inf"						)						)						)
           if bigram not in self.bpe_ranks:
                break
           UpperCamelCase__    ,					UpperCamelCase__      :       List[str]	    =  bigram
           UpperCamelCase__      :       Union[str, Any]	    =  []
           UpperCamelCase__      :       List[Any]	    =  0
           while i < len(SCREAMING_SNAKE_CASE						):
                try:
                     UpperCamelCase__      :       Optional[int]	    =  word.index(SCREAMING_SNAKE_CASE							,       SCREAMING_SNAKE_CASE						)
                except ValueError:
                     new_word.extend(word[i:]						)
                     break
                else:
                     new_word.extend(word[i:j]						)
                     UpperCamelCase__      :       Union[str, Any]	    =  j

                if word[i] == first and i < len(SCREAMING_SNAKE_CASE						) - 1 and word[i + 1] == second:
                     new_word.append(first + second						)
                     i += 2
                else:
                     new_word.append(word[i]						)
                     i += 1
           UpperCamelCase__      :       Union[str, Any]	    =  tuple(SCREAMING_SNAKE_CASE						)
           UpperCamelCase__      :       Optional[Any]	    =  new_word
           if len(SCREAMING_SNAKE_CASE						) == 1:
                break
           else:
                UpperCamelCase__      :       str	    =  get_pairs(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Any	    =  " ".join(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Optional[int]	    =  word
      return word







 def  __lowercase (		self :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       Any						):


      '''simple docstring'''






      UpperCamelCase__      :       int	    =  []
      for token in re.findall(self.pat							,       SCREAMING_SNAKE_CASE						):
           UpperCamelCase__      :       Optional[int]	    =  "".join(
               self.byte_encoder[b] for b in token.encode("utf-8"						)						)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
           bpe_tokens.extend(bpe_token for bpe_token in self.bpe(SCREAMING_SNAKE_CASE						).split(" "						)						)
      return bpe_tokens







 def  __lowercase (		self :       Union[str, Any]							,       SCREAMING_SNAKE_CASE :       Tuple						):


      '''simple docstring'''






      return self.encoder.get(SCREAMING_SNAKE_CASE							,       self.encoder.get(self.unk_token						)						)







 def  __lowercase (		self :       Tuple							,       SCREAMING_SNAKE_CASE :       Union[str, Any]						):


      '''simple docstring'''






      return self.decoder.get(SCREAMING_SNAKE_CASE						)







 def  __lowercase (		self :       List[str]							,       SCREAMING_SNAKE_CASE :       int						):


      '''simple docstring'''






      UpperCamelCase__      :       str	    =  "".join(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Optional[int]	    =  bytearray([self.byte_decoder[c] for c in text]						).decode("utf-8"							,       errors=self.errors						)
      return text







 def  __lowercase (		self :       int							,       SCREAMING_SNAKE_CASE :       str							,       SCREAMING_SNAKE_CASE :       Optional[str] = None						):


      '''simple docstring'''






      if not os.path.isdir(SCREAMING_SNAKE_CASE						):
           logger.error(F'Vocabulary path ({save_directory}) should be a directory'						)
           return
      UpperCamelCase__      :       List[str]	    =  os.path.join(
          SCREAMING_SNAKE_CASE							,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
      UpperCamelCase__      :       Any	    =  os.path.join(
          SCREAMING_SNAKE_CASE							,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]						)

      with open(SCREAMING_SNAKE_CASE							,       "w"							,       encoding="utf-8"						) as f:
           f.write(json.dumps(self.encoder							,       indent=2							,       sort_keys=SCREAMING_SNAKE_CASE							,       ensure_ascii=SCREAMING_SNAKE_CASE						) + "\n"						)

      UpperCamelCase__      :       List[Any]	    =  0
      with open(SCREAMING_SNAKE_CASE							,       "w"							,       encoding="utf-8"						) as writer:
           writer.write("#version: 0.2\n"						)
           for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,       key=lambda SCREAMING_SNAKE_CASE						: kv[1]						):
                if index != token_index:
                     logger.warning(
                         F'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                         " Please check that the tokenizer is not corrupted!"						)
                     UpperCamelCase__      :       Optional[Any]	    =  token_index
                writer.write(" ".join(SCREAMING_SNAKE_CASE						) + "\n"						)
                index += 1

      return vocab_file, merge_file







 def  __lowercase (		self :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       List[int]							,       SCREAMING_SNAKE_CASE :       Optional[List[int]] = None							,       SCREAMING_SNAKE_CASE :       bool = False						):


      '''simple docstring'''






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

      if token_ids_a is None:
           return [1] + ([0] * len(SCREAMING_SNAKE_CASE						)) + [1]
      return [1] + ([0] * len(SCREAMING_SNAKE_CASE						)) + [1, 1] + ([0] * len(SCREAMING_SNAKE_CASE						)) + [1]







 def  __lowercase (		self :       Dict							,       SCREAMING_SNAKE_CASE :       List[int]							,       SCREAMING_SNAKE_CASE :       Optional[List[int]] = None						):


      '''simple docstring'''






      UpperCamelCase__      :       Tuple	    =  [self.sep_token_id]
      UpperCamelCase__      :       List[Any]	    =  [self.cls_token_id]

      if token_ids_a is None:
           return len(cls + token_ids_a + sep						) * [0]
      return len(cls + token_ids_a + sep + sep + token_ids_a + sep						) * [0]







 def  __lowercase (		self :       str							,       SCREAMING_SNAKE_CASE :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       Union[str, Any]=False							,       **SCREAMING_SNAKE_CASE :       Optional[Any]						):


      '''simple docstring'''






      UpperCamelCase__      :       int	    =  kwargs.pop("add_prefix_space"							,       self.add_prefix_space						)
      if (is_split_into_words or add_prefix_space) and (len(SCREAMING_SNAKE_CASE						) > 0 and not text[0].isspace()):
           UpperCamelCase__      :       Optional[Any]	    =  " " + text
      return (text, kwargs)







 def  __lowercase (		self :       List[str]							,       SCREAMING_SNAKE_CASE :       List[int]							,       SCREAMING_SNAKE_CASE :       Optional[List[int]] = None						):


      '''simple docstring'''






      return token_ids_a + [self.eos_token_id]







 def  __lowercase (		self :       Optional[Any]							,       SCREAMING_SNAKE_CASE :       "Conversation"						):


      '''simple docstring'''






      UpperCamelCase__      :       int	    =  []
      for is_user, text in conversation.iter_texts():
           if is_user:
                # We need to space prefix as it's being done within blenderbot
                inputs.append(" " + text						)
           else:
                # Generated responses should contain them already.
                inputs.append(SCREAMING_SNAKE_CASE						)

      UpperCamelCase__      :       Any	    =  "  ".join(SCREAMING_SNAKE_CASE						)
      UpperCamelCase__      :       Dict	    =  self.encode(SCREAMING_SNAKE_CASE						)
      if len(SCREAMING_SNAKE_CASE						) > self.model_max_length:
           UpperCamelCase__      :       str	    =  input_ids[-self.model_max_length :]
           logger.warning(F'Trimmed input from conversation as it was longer than {self.model_max_length} tokens.'						)
      return input_ids







from __future__ import annotations







def 		SCREAMING_SNAKE_CASE							( __lowerCAmelCase ,   __lowerCAmelCase      )			->     list[int]:
     UpperCamelCase__      :       Optional[Any]	    =  0
     UpperCamelCase__      :       Any	    =  len(__lowerCAmelCase      ) - 1

     while i < j:
          if nums[i] + nums[j] == target:
               return [i, j]
          elif nums[i] + nums[j] < target:
               UpperCamelCase__      :       Optional[int]	    =  i + 1
          else:
               UpperCamelCase__      :       Dict	    =  j - 1

     return []


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 print(F"""{two_pointer([2, 7, 11, 15], 9) = }""")