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

snake_case__				= logging.get_logger(__name__)


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

snake_case__				= {
    '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'
    },
}

snake_case__				= {'facebook/blenderbot-3B': 128}
@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def       __magic_name__(  )						->    List[str]:



      '''simple docstring'''

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



      '''simple docstring'''

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




class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     A_										=  VOCAB_FILES_NAMES
     A_										=  PRETRAINED_VOCAB_FILES_MAP
     A_										=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     A_										=  ['input_ids', 'attention_mask']



     def __init__(					self				,				A_				,				A_				,				A_="replace"				,				A_="<s>"				,				A_="</s>"				,				A_="</s>"				,				A_="<s>"				,				A_="<unk>"				,				A_="<pad>"				,				A_="<mask>"				,				A_=False				,				**A_				,				) ->				Tuple:






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

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

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

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

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           _lowerCamelCase			    =				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 		UpperCamelCase_						(					self						) ->				Dict:






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



     def 		UpperCamelCase_						(					self						) ->				int:






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



     def 		UpperCamelCase_						(					self				,				A_						) ->				Dict:






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

           if not pairs:
                 return token

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

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



     def 		UpperCamelCase_						(					self				,				A_						) ->				int:






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



     def 		UpperCamelCase_						(					self				,				A_						) ->				Union[str, Any]:






           """simple docstring"""
           return self.encoder.get(A_				,				self.encoder.get(self.unk_token						)						)



     def 		UpperCamelCase_						(					self				,				A_						) ->				str:






           """simple docstring"""
           return self.decoder.get(A_						)



     def 		UpperCamelCase_						(					self				,				A_						) ->				Tuple:






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



     def 		UpperCamelCase_						(					self				,				A_				,				A_ = None						) ->				Tuple[str]:






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

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

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

           return vocab_file, merge_file



     def 		UpperCamelCase_						(					self				,				A_				,				A_ = None				,				A_ = False						) ->				List[int]:






           """simple docstring"""
           if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=A_				,				token_ids_a=A_				,				already_has_special_tokens=A_						)

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



     def 		UpperCamelCase_						(					self				,				A_				,				A_ = None						) ->				List[int]:






           """simple docstring"""
           _lowerCamelCase			    =				[self.sep_token_id]
           _lowerCamelCase			    =				[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 		UpperCamelCase_						(					self				,				A_				,				A_=False				,				**A_						) ->				Tuple:






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



     def 		UpperCamelCase_						(					self				,				A_				,				A_ = None						) ->				Tuple:






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





     def 		UpperCamelCase_						(					self				,				A_						) ->				List[int]:






           """simple docstring"""
           _lowerCamelCase			    =				[]
           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(A_						)

           _lowerCamelCase			    =				'''  '''.join(A_						)
           _lowerCamelCase			    =				self.encode(A_						)
           if len(A_						) > self.model_max_length:
                 _lowerCamelCase			    =				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
import warnings

from ...utils import logging
from .image_processing_dpt import DPTImageProcessor


snake_case__				= logging.get_logger(__name__)



class  UpperCamelCase				( __lowercase ):

     '''simple docstring'''

     def __init__(					self				,				*A_				,				**A_						) ->				None:






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