






"""simple docstring"""


import warnings

from ...utils import logging
from .image_processing_flava import FlavaImageProcessor


lowercase_				     =     logging.get_logger(__name__)


class 					snake_case		(							_lowerCAmelCase						):


   '''simple docstring'''

   def __init__(	self :     Optional[int],       *_lowerCamelCase :     List[Any],       **_lowerCamelCase :     Optional[int]  ):

     '''simple docstring'''
     warnings.warn(
         '''The class FlavaFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'''
         ''' use FlavaImageProcessor instead.''',       _lowerCamelCase,       )
     super().__init__(*_lowerCamelCase,       **_lowerCamelCase  )












"""simple docstring"""


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

lowercase_				     =     logging.get_logger(__name__)


lowercase_				     =     {
    'vocab_file': 'vocab.json',
    'merges_file': 'merges.txt',
    'tokenizer_config_file': 'tokenizer_config.json',
}

lowercase_				     =     {
    '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'
    },
}

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



@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def 					lowerCAmelCase				(    ):




  """simple docstring"""







  __A									= (
      list(range(ord('''!''' )		,       ord('''~''' ) + 1 ) ) + list(range(ord('''¡''' )		,       ord('''¬''' ) + 1 ) ) + list(range(ord('''®''' )		,       ord('''ÿ''' ) + 1 ) )
  )
  __A									= bs[:]
  __A									= 0
  for b in range(2**8 ):
    if b not in bs:
      bs.append(__UpperCamelCase )
      cs.append(2**8 + n )
      n += 1
  __A									= [chr(__UpperCamelCase ) for n in cs]
  return dict(zip(__UpperCamelCase		,       __UpperCamelCase ) )



def 					lowerCAmelCase				(    __UpperCamelCase ):




  """simple docstring"""







  __A									= set()
  __A									= word[0]
  for char in word[1:]:
    pairs.add((prev_char, char) )
    __A									= char
  return pairs





class 					snake_case		(							_lowerCAmelCase						):


   '''simple docstring'''

   A_						:	Tuple						 = VOCAB_FILES_NAMES
   A_						:	Union[str, Any]						 = PRETRAINED_VOCAB_FILES_MAP
   A_						:	str						 = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A_						:	Optional[Any]						 = ["input_ids", "attention_mask"]


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

     '''simple docstring'''
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else bos_token
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else eos_token
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else sep_token
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else cls_token
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else unk_token
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else pad_token

     # Mask token behave like a normal word, i.e. include the space before it
     __A									= AddedToken(_lowerCamelCase,       lstrip=_lowerCamelCase,       rstrip=_lowerCamelCase  ) if isinstance(_lowerCamelCase,       _lowerCamelCase  ) else mask_token

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

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

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     __A									= 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 				_SCREAMING_SNAKE_CASE				(	self :     Any  ):

     '''simple docstring'''
     return len(self.encoder  )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Union[str, Any]  ):

     '''simple docstring'''
     return dict(self.encoder,       **self.added_tokens_encoder  )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[Any],       _lowerCamelCase :     List[Any]  ):

     '''simple docstring'''
     if token in self.cache:
       return self.cache[token]
     __A									= tuple(_lowerCamelCase  )
     __A									= get_pairs(_lowerCamelCase  )

     if not pairs:
       return token

     while True:
       __A									= min(_lowerCamelCase,       key=lambda _lowerCamelCase  : self.bpe_ranks.get(_lowerCamelCase,       float('''inf'''  )  )  )
       if bigram not in self.bpe_ranks:
         break
       __A			,    __A									= bigram
       __A									= []
       __A									= 0
       while i < len(_lowerCamelCase  ):
         try:
           __A									= word.index(_lowerCamelCase,       _lowerCamelCase  )
         except ValueError:
           new_word.extend(word[i:]  )
           break
         else:
           new_word.extend(word[i:j]  )
           __A									= j

         if word[i] == first and i < len(_lowerCamelCase  ) - 1 and word[i + 1] == second:
           new_word.append(first + second  )
           i += 2
         else:
           new_word.append(word[i]  )
           i += 1
       __A									= tuple(_lowerCamelCase  )
       __A									= new_word
       if len(_lowerCamelCase  ) == 1:
         break
       else:
         __A									= get_pairs(_lowerCamelCase  )
     __A									= ''' '''.join(_lowerCamelCase  )
     __A									= word
     return word


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[int],       _lowerCamelCase :     Dict  ):

     '''simple docstring'''
     __A									= []
     for token in re.findall(self.pat,       _lowerCamelCase  ):
       __A									= ''''''.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(_lowerCamelCase  ).split(''' '''  )  )
     return bpe_tokens


   def 				_SCREAMING_SNAKE_CASE				(	self :     Union[str, Any],       _lowerCamelCase :     Dict  ):

     '''simple docstring'''
     return self.encoder.get(_lowerCamelCase,       self.encoder.get(self.unk_token  )  )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[int],       _lowerCamelCase :     Any  ):

     '''simple docstring'''
     return self.decoder.get(_lowerCamelCase  )


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[Any],       _lowerCamelCase :     Dict  ):

     '''simple docstring'''
     __A									= ''''''.join(_lowerCamelCase  )
     __A									= bytearray([self.byte_decoder[c] for c in text]  ).decode('''utf-8''',       errors=self.errors  )
     return text


   def 				_SCREAMING_SNAKE_CASE				(	self :     Dict,       _lowerCamelCase :     str,       _lowerCamelCase :     Optional[str] = None  ):

     '''simple docstring'''
     if not os.path.isdir(_lowerCamelCase  ):
       logger.error(f'Vocabulary path ({save_directory}) should be a directory'  )
       return
     __A									= os.path.join(
         _lowerCamelCase,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
     __A									= os.path.join(
         _lowerCamelCase,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']  )

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

     __A									= 0
     with open(_lowerCamelCase,       '''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 _lowerCamelCase  : 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!'''  )
           __A									= token_index
         writer.write(''' '''.join(_lowerCamelCase  ) + '''\n'''  )
         index += 1

     return vocab_file, merge_file


   def 				_SCREAMING_SNAKE_CASE				(	self :     Optional[int],       _lowerCamelCase :     List[int],       _lowerCamelCase :     Optional[List[int]] = None,       _lowerCamelCase :     bool = 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  )

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


   def 				_SCREAMING_SNAKE_CASE				(	self :     Any,       _lowerCamelCase :     List[int],       _lowerCamelCase :     Optional[List[int]] = None  ):

     '''simple docstring'''
     __A									= [self.sep_token_id]
     __A									= [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 				_SCREAMING_SNAKE_CASE				(	self :     Optional[Any],       _lowerCamelCase :     Union[str, Any],       _lowerCamelCase :     List[str]=False,       **_lowerCamelCase :     List[Any]  ):

     '''simple docstring'''
     __A									= kwargs.pop('''add_prefix_space''',       self.add_prefix_space  )
     if (is_split_into_words or add_prefix_space) and (len(_lowerCamelCase  ) > 0 and not text[0].isspace()):
       __A									= ''' ''' + text
     return (text, kwargs)


   def 				_SCREAMING_SNAKE_CASE				(	self :     Union[str, Any],       _lowerCamelCase :     List[int],       _lowerCamelCase :     Optional[List[int]] = None  ):

     '''simple docstring'''
     return token_ids_a + [self.eos_token_id]






   def 				_SCREAMING_SNAKE_CASE				(	self :     List[Any],       _lowerCamelCase :     "Conversation"  ):

     '''simple docstring'''
     __A									= []
     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(_lowerCamelCase  )

     __A									= '''  '''.join(_lowerCamelCase  )
     __A									= self.encode(_lowerCamelCase  )
     if len(_lowerCamelCase  ) > self.model_max_length:
       __A									= 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




