






'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a_					= logging.get_logger(__name__)


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

a_					= {
    'vocab_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json'
    },
    'merges_file': {
        'facebook/blenderbot_small-90M': 'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt'
    },
    'tokenizer_config_file': {
        'facebook/blenderbot_small-90M': (
            'https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json'
        )
    },
}

a_					= {'facebook/blenderbot_small-90M': 5_1_2}





def  _a(  UpperCamelCase__				:						Optional[int]							):




 '''simple docstring'''






 SCREAMING_SNAKE_CASE__     :				Optional[int]									=set()
 SCREAMING_SNAKE_CASE__     :				Optional[Any]									=word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)							)
  SCREAMING_SNAKE_CASE__     :				List[Any]									=char

 SCREAMING_SNAKE_CASE__     :				Any									=set(UpperCamelCase__							)
 return pairs







class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase				):
 snake_case_  							=							VOCAB_FILES_NAMES
 snake_case_  							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_  							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_  							=							["""input_ids""", """attention_mask"""]




 def __init__(      self	:							Optional[int]					,      __lowercase	:							List[str]					,      __lowercase	:							Dict					,      __lowercase	:							Optional[int]="__start__"					,      __lowercase	:							Union[str, Any]="__end__"					,      __lowercase	:							int="__unk__"					,      __lowercase	:							Union[str, Any]="__null__"					,      **__lowercase	:							Optional[Any]					,      )	->						int:
  super().__init__(unk_token=__lowercase					,      bos_token=__lowercase					,      eos_token=__lowercase					,      pad_token=__lowercase					,      **__lowercase      )

  with open(__lowercase					,      encoding='''utf-8'''      ) as vocab_handle:
   SCREAMING_SNAKE_CASE__     :				Optional[int]									=json.load(__lowercase      )
  SCREAMING_SNAKE_CASE__     :				str									={v: k for k, v in self.encoder.items()}
  with open(__lowercase					,      encoding='''utf-8'''      ) as merges_handle:
   SCREAMING_SNAKE_CASE__     :				Dict									=merges_handle.read().split('''\n'''      )[1:-1]
  SCREAMING_SNAKE_CASE__     :				Tuple									=[tuple(merge.split()      ) for merge in merges]
  SCREAMING_SNAKE_CASE__     :				Dict									=dict(zip(__lowercase					,      range(len(__lowercase      )      )      )      )
  SCREAMING_SNAKE_CASE__     :				str									={}




 @property
 def      __magic_name__	(      self	:							Union[str, Any]      )	->						int:
  return len(self.encoder      )




 def      __magic_name__	(      self	:							List[str]      )	->						Dict:
  return dict(self.encoder					,      **self.added_tokens_encoder      )




 def      __magic_name__	(      self	:							Optional[Any]					,      __lowercase	:							str      )	->						str:
  if token in self.cache:
   return self.cache[token]
  SCREAMING_SNAKE_CASE__     :				Dict									=re.sub('''([.,!?()])'''					,      r''' \1'''					,      __lowercase      )
  SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=re.sub('''(\')'''					,      r''' \1 '''					,      __lowercase      )
  SCREAMING_SNAKE_CASE__     :				Optional[int]									=re.sub(r'''\s{2,}'''					,      ''' '''					,      __lowercase      )
  if "\n" in token:
   SCREAMING_SNAKE_CASE__     :				Any									=token.replace('''\n'''					,      ''' __newln__'''      )

  SCREAMING_SNAKE_CASE__     :				Dict									=token.split(''' '''      )
  SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[]
  for token in tokens:
   if not len(__lowercase      ):
    continue

   SCREAMING_SNAKE_CASE__     :				Optional[int]									=token.lower()
   SCREAMING_SNAKE_CASE__     :				Optional[int]									=tuple(__lowercase      )
   SCREAMING_SNAKE_CASE__     :				List[str]									=tuple(list(word[:-1]      ) + [word[-1] + '''</w>''']      )
   SCREAMING_SNAKE_CASE__     :				int									=get_pairs(__lowercase      )

   if not pairs:
    words.append(__lowercase      )
    continue

   while True:
    SCREAMING_SNAKE_CASE__     :				str									=min(__lowercase					,      key=lambda __lowercase      : self.bpe_ranks.get(__lowercase					,      float('''inf'''      )      )      )
    if bigram not in self.bpe_ranks:
     break
    SCREAMING_SNAKE_CASE__     :				Optional[int]									=bigram
    SCREAMING_SNAKE_CASE__     :				int									=[]
    SCREAMING_SNAKE_CASE__     :				str									=0

    while i < len(__lowercase      ):
     try:
      SCREAMING_SNAKE_CASE__     :				List[Any]									=word.index(__lowercase					,      __lowercase      )
      new_word.extend(word[i:j]      )
      SCREAMING_SNAKE_CASE__     :				List[str]									=j
     except ValueError:
      new_word.extend(word[i:]      )
      break

     if word[i] == first and i < len(__lowercase      ) - 1 and word[i + 1] == second:
      new_word.append(first + second      )
      i += 2
     else:
      new_word.append(word[i]      )
      i += 1
    SCREAMING_SNAKE_CASE__     :				Any									=tuple(__lowercase      )
    SCREAMING_SNAKE_CASE__     :				Optional[Any]									=new_word
    if len(__lowercase      ) == 1:
     break
    else:
     SCREAMING_SNAKE_CASE__     :				Dict									=get_pairs(__lowercase      )
   SCREAMING_SNAKE_CASE__     :				Dict									='''@@ '''.join(__lowercase      )
   SCREAMING_SNAKE_CASE__     :				Optional[Any]									=word[:-4]

   SCREAMING_SNAKE_CASE__     :				Any									=word
   words.append(__lowercase      )
  return " ".join(__lowercase      )




 def      __magic_name__	(      self	:							Tuple					,      __lowercase	:							str      )	->						List[str]:
  SCREAMING_SNAKE_CASE__     :				int									=[]

  SCREAMING_SNAKE_CASE__     :				str									=re.findall(r'''\S+\n?'''					,      __lowercase      )

  for token in words:
   split_tokens.extend(list(self.bpe(__lowercase      ).split(''' '''      )      )      )
  return split_tokens




 def      __magic_name__	(      self	:							Optional[int]					,      __lowercase	:							str      )	->						int:
  SCREAMING_SNAKE_CASE__     :				Any									=token.lower()
  return self.encoder.get(__lowercase					,      self.encoder.get(self.unk_token      )      )




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							int      )	->						str:
  return self.decoder.get(__lowercase					,      self.unk_token      )




 def      __magic_name__	(      self	:							str					,      __lowercase	:							List[str]      )	->						str:
  SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=''' '''.join(__lowercase      ).replace('''@@ '''					,      ''''''      ).strip()
  return out_string




 def      __magic_name__	(      self	:							List[str]					,      __lowercase	:							str					,      __lowercase	:							Optional[str] = None      )	->						Tuple[str]:
  if not os.path.isdir(__lowercase      ):
   logger.error(F"Vocabulary path ({save_directory}) should be a directory"      )
   return
  SCREAMING_SNAKE_CASE__     :				List[Any]									=os.path.join(
      __lowercase					,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']      )
  SCREAMING_SNAKE_CASE__     :				int									=os.path.join(
      __lowercase					,      (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']      )

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

  SCREAMING_SNAKE_CASE__     :				Dict									=0
  with open(__lowercase					,      '''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 __lowercase      : 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!'''      )
     SCREAMING_SNAKE_CASE__     :				Optional[int]									=token_index
    writer.write(''' '''.join(__lowercase      ) + '''\n'''      )
    index += 1

  return vocab_file, merge_file







'''simple docstring'''
import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer


a_					= logging.get_logger(__name__)

a_					= {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

a_					= {
    'vocab_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/vocab.txt',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/vocab.txt',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/vocab.txt',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/vocab.txt',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/vocab.txt'
        ),
        'bert-base-multilingual-cased': 'https://huggingface.co/bert-base-multilingual-cased/resolve/main/vocab.txt',
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/vocab.txt',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/vocab.txt',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/vocab.txt'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/vocab.txt'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/vocab.txt'
        ),
        'bert-base-german-dbmdz-cased': 'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/vocab.txt',
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/vocab.txt'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/vocab.txt'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'bert-base-uncased': 'https://huggingface.co/bert-base-uncased/resolve/main/tokenizer.json',
        'bert-large-uncased': 'https://huggingface.co/bert-large-uncased/resolve/main/tokenizer.json',
        'bert-base-cased': 'https://huggingface.co/bert-base-cased/resolve/main/tokenizer.json',
        'bert-large-cased': 'https://huggingface.co/bert-large-cased/resolve/main/tokenizer.json',
        'bert-base-multilingual-uncased': (
            'https://huggingface.co/bert-base-multilingual-uncased/resolve/main/tokenizer.json'
        ),
        'bert-base-multilingual-cased': (
            'https://huggingface.co/bert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-chinese': 'https://huggingface.co/bert-base-chinese/resolve/main/tokenizer.json',
        'bert-base-german-cased': 'https://huggingface.co/bert-base-german-cased/resolve/main/tokenizer.json',
        'bert-large-uncased-whole-word-masking': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking': (
            'https://huggingface.co/bert-large-cased-whole-word-masking/resolve/main/tokenizer.json'
        ),
        'bert-large-uncased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-uncased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-large-cased-whole-word-masking-finetuned-squad': (
            'https://huggingface.co/bert-large-cased-whole-word-masking-finetuned-squad/resolve/main/tokenizer.json'
        ),
        'bert-base-cased-finetuned-mrpc': (
            'https://huggingface.co/bert-base-cased-finetuned-mrpc/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-cased': (
            'https://huggingface.co/bert-base-german-dbmdz-cased/resolve/main/tokenizer.json'
        ),
        'bert-base-german-dbmdz-uncased': (
            'https://huggingface.co/bert-base-german-dbmdz-uncased/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-cased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-cased-v1/resolve/main/tokenizer.json'
        ),
        'TurkuNLP/bert-base-finnish-uncased-v1': (
            'https://huggingface.co/TurkuNLP/bert-base-finnish-uncased-v1/resolve/main/tokenizer.json'
        ),
        'wietsedv/bert-base-dutch-cased': (
            'https://huggingface.co/wietsedv/bert-base-dutch-cased/resolve/main/tokenizer.json'
        ),
    },
}

a_					= {
    'bert-base-uncased': 5_1_2,
    'bert-large-uncased': 5_1_2,
    'bert-base-cased': 5_1_2,
    'bert-large-cased': 5_1_2,
    'bert-base-multilingual-uncased': 5_1_2,
    'bert-base-multilingual-cased': 5_1_2,
    'bert-base-chinese': 5_1_2,
    'bert-base-german-cased': 5_1_2,
    'bert-large-uncased-whole-word-masking': 5_1_2,
    'bert-large-cased-whole-word-masking': 5_1_2,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 5_1_2,
    'bert-large-cased-whole-word-masking-finetuned-squad': 5_1_2,
    'bert-base-cased-finetuned-mrpc': 5_1_2,
    'bert-base-german-dbmdz-cased': 5_1_2,
    'bert-base-german-dbmdz-uncased': 5_1_2,
    'TurkuNLP/bert-base-finnish-cased-v1': 5_1_2,
    'TurkuNLP/bert-base-finnish-uncased-v1': 5_1_2,
    'wietsedv/bert-base-dutch-cased': 5_1_2,
}

a_					= {
    'bert-base-uncased': {'do_lower_case': True},
    'bert-large-uncased': {'do_lower_case': True},
    'bert-base-cased': {'do_lower_case': False},
    'bert-large-cased': {'do_lower_case': False},
    'bert-base-multilingual-uncased': {'do_lower_case': True},
    'bert-base-multilingual-cased': {'do_lower_case': False},
    'bert-base-chinese': {'do_lower_case': False},
    'bert-base-german-cased': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking': {'do_lower_case': False},
    'bert-large-uncased-whole-word-masking-finetuned-squad': {'do_lower_case': True},
    'bert-large-cased-whole-word-masking-finetuned-squad': {'do_lower_case': False},
    'bert-base-cased-finetuned-mrpc': {'do_lower_case': False},
    'bert-base-german-dbmdz-cased': {'do_lower_case': False},
    'bert-base-german-dbmdz-uncased': {'do_lower_case': True},
    'TurkuNLP/bert-base-finnish-cased-v1': {'do_lower_case': False},
    'TurkuNLP/bert-base-finnish-uncased-v1': {'do_lower_case': True},
    'wietsedv/bert-base-dutch-cased': {'do_lower_case': False},
}






class      __SCREAMING_SNAKE_CASE      (			lowerCamelCase				):
 snake_case_  							=							VOCAB_FILES_NAMES
 snake_case_  							=							PRETRAINED_VOCAB_FILES_MAP
 snake_case_  							=							PRETRAINED_INIT_CONFIGURATION
 snake_case_  							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 snake_case_  							=							BertTokenizer




 def __init__(      self	:							int					,      __lowercase	:							Union[str, Any]=None					,      __lowercase	:							Tuple=None					,      __lowercase	:							str=True					,      __lowercase	:							Optional[Any]="[UNK]"					,      __lowercase	:							Tuple="[SEP]"					,      __lowercase	:							Any="[PAD]"					,      __lowercase	:							List[Any]="[CLS]"					,      __lowercase	:							Union[str, Any]="[MASK]"					,      __lowercase	:							Tuple=True					,      __lowercase	:							str=None					,      **__lowercase	:							Any					,      )	->						Optional[Any]:
       super().__init__(
           __lowercase					,      tokenizer_file=__lowercase					,      do_lower_case=__lowercase					,      unk_token=__lowercase					,      sep_token=__lowercase					,      pad_token=__lowercase					,      cls_token=__lowercase					,      mask_token=__lowercase					,      tokenize_chinese_chars=__lowercase					,      strip_accents=__lowercase					,      **__lowercase					,      )

       SCREAMING_SNAKE_CASE__     :				str									=json.loads(self.backend_tokenizer.normalizer.__getstate__()      )
       if (
           normalizer_state.get('''lowercase'''					,      __lowercase      ) != do_lower_case
           or normalizer_state.get('''strip_accents'''					,      __lowercase      ) != strip_accents
           or normalizer_state.get('''handle_chinese_chars'''					,      __lowercase      ) != tokenize_chinese_chars
       ):
             SCREAMING_SNAKE_CASE__     :				int									=getattr(__lowercase					,      normalizer_state.pop('''type'''      )      )
             SCREAMING_SNAKE_CASE__     :				Any									=do_lower_case
             SCREAMING_SNAKE_CASE__     :				Any									=strip_accents
             SCREAMING_SNAKE_CASE__     :				Dict									=tokenize_chinese_chars
             SCREAMING_SNAKE_CASE__     :				Union[str, Any]									=normalizer_class(**__lowercase      )

       SCREAMING_SNAKE_CASE__     :				Optional[int]									=do_lower_case




 def      __magic_name__	(      self	:							int					,      __lowercase	:							Optional[Any]					,      __lowercase	:							Union[str, Any]=None      )	->						int:
       SCREAMING_SNAKE_CASE__     :				Optional[Any]									=[self.cls_token_id] + token_ids_a + [self.sep_token_id]

       if token_ids_a:
             output += token_ids_a + [self.sep_token_id]

       return output




 def      __magic_name__	(      self	:							Union[str, Any]					,      __lowercase	:							List[int]					,      __lowercase	:							Optional[List[int]] = None      )	->						List[int]:
       SCREAMING_SNAKE_CASE__     :				List[str]									=[self.sep_token_id]
       SCREAMING_SNAKE_CASE__     :				Optional[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      ) * [0] + len(token_ids_a + sep      ) * [1]




 def      __magic_name__	(      self	:							List[Any]					,      __lowercase	:							str					,      __lowercase	:							Optional[str] = None      )	->						Tuple[str]:
       SCREAMING_SNAKE_CASE__     :				Optional[int]									=self._tokenizer.model.save(__lowercase					,      name=__lowercase      )
       return tuple(__lowercase      )