



'''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


_UpperCamelCase											=		logging.get_logger(__name__)

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

_UpperCamelCase											=		{
    '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'
        ),
    },
}

_UpperCamelCase											=		{
    'bert-base-uncased': 512,
    'bert-large-uncased': 512,
    'bert-base-cased': 512,
    'bert-large-cased': 512,
    'bert-base-multilingual-uncased': 512,
    'bert-base-multilingual-cased': 512,
    'bert-base-chinese': 512,
    'bert-base-german-cased': 512,
    'bert-large-uncased-whole-word-masking': 512,
    'bert-large-cased-whole-word-masking': 512,
    'bert-large-uncased-whole-word-masking-finetuned-squad': 512,
    'bert-large-cased-whole-word-masking-finetuned-squad': 512,
    'bert-base-cased-finetuned-mrpc': 512,
    'bert-base-german-dbmdz-cased': 512,
    'bert-base-german-dbmdz-uncased': 512,
    'TurkuNLP/bert-base-finnish-cased-v1': 512,
    'TurkuNLP/bert-base-finnish-uncased-v1': 512,
    'wietsedv/bert-base-dutch-cased': 512,
}

_UpperCamelCase											=		{
    '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    lowerCamelCase_       (							SCREAMING_SNAKE_CASE_	):
  """simple docstring"""




  a_				   =VOCAB_FILES_NAMES
  a_				   =PRETRAINED_VOCAB_FILES_MAP
  a_				   =PRETRAINED_INIT_CONFIGURATION
  a_				   =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  a_				   =BertTokenizer




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

    __lowerCamelCase			:			Tuple       			=					json.loads(self.backend_tokenizer.normalizer.__getstate__()  )
    if (
        normalizer_state.get('lowercase'     ,      _a  ) != do_lower_case
        or normalizer_state.get('strip_accents'     ,      _a  ) != strip_accents
        or normalizer_state.get('handle_chinese_chars'     ,      _a  ) != tokenize_chinese_chars
    ):
      __lowerCamelCase			:			List[str]       			=					getattr(_a     ,      normalizer_state.pop('type'  )  )
      __lowerCamelCase			:			Union[str, Any]       			=					do_lower_case
      __lowerCamelCase			:			Optional[Any]       			=					strip_accents
      __lowerCamelCase			:			Any       			=					tokenize_chinese_chars
      __lowerCamelCase			:			Optional[Any]       			=					normalizer_class(**_a  )

    __lowerCamelCase			:			Optional[int]       			=					do_lower_case




  def 		_lowercase	(					self :      Union[str, Any]     ,      _a :      Dict     ,      _a :      List[str]=None  )   ->   Tuple:
    __lowerCamelCase			:			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 		_lowercase	(					self :      Tuple     ,      _a :      List[int]     ,      _a :      Optional[List[int]] = None  )   ->   List[int]:
    __lowerCamelCase			:			Any       			=					[self.sep_token_id]
    __lowerCamelCase			:			List[str]       			=					[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 		_lowercase	(					self :      int     ,      _a :      str     ,      _a :      Optional[str] = None  )   ->   Tuple[str]:
    __lowerCamelCase			:			Dict       			=					self._tokenizer.model.save(_a     ,      name=_a  )
    return tuple(_a  )











'''simple docstring'''





import string

def 			a_	(				_lowerCAmelCase			) -> str:
  __lowerCamelCase			:			Union[str, Any]       			=					''
  for i in sequence:
    __lowerCamelCase			:			Tuple       			=					ord(_lowerCAmelCase			)
    if 65 <= extract <= 90:
      output += chr(155 - extract			)
    elif 97 <= extract <= 122:
      output += chr(219 - extract			)
    else:
      output += i
  return output

def 			a_	(				_lowerCAmelCase			) -> str:
  __lowerCamelCase			:			Optional[Any]       			=					string.ascii_letters
  __lowerCamelCase			:			str       			=					string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
  return "".join(
      letters_reversed[letters.index(_lowerCAmelCase			)] if c in letters else c for c in sequence			)

def 			a_	(				) -> None:
  from timeit import timeit

  print('Running performance benchmarks...'			)
  __lowerCamelCase			:			Tuple       			=					'from string import printable ; from __main__ import atbash, atbash_slow'
  print(F'> atbash_slow(): {timeit("atbash_slow(printable)"			,setup=_lowerCAmelCase			)} seconds'			)
  print(F'>      atbash(): {timeit("atbash(printable)"			,setup=_lowerCAmelCase			)} seconds'			)


if __name__ == "__main__":
   for example in ("ABCDEFGH", "123GGjj", "testStringtest", "with space"):
      print(f'''{example} encrypted in atbash: {atbash(example)}''')
   benchmark()






