

import string




def 			UpperCAmelCase__				(			_A      : str							):





  '''simple docstring'''







  a__  =''''''
  for i in sequence:
    a__  =ord(_A							)
    if 65 <= extract <= 90:
      output += chr(1_55 - extract							)
    elif 97 <= extract <= 1_22:
      output += chr(2_19 - extract							)
    else:
      output += i
  return output




def 			UpperCAmelCase__				(			_A      : str							):





  '''simple docstring'''







  a__  =string.ascii_letters
  a__  =string.ascii_lowercase[::-1] + string.ascii_uppercase[::-1]
  return "".join(
      letters_reversed[letters.index(_A							)] if c in letters else c for c in sequence							)




def 			UpperCAmelCase__				(			):





  '''simple docstring'''







  from timeit import timeit

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


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



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase           =					{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase           =					[
           '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
           '''CanineForMultipleChoice''',
           '''CanineForQuestionAnswering''',
           '''CanineForSequenceClassification''',
           '''CanineForTokenClassification''',
           '''CanineLayer''',
           '''CanineModel''',
           '''CaninePreTrainedModel''',
           '''load_tf_weights_in_canine''',
       ]


if TYPE_CHECKING:
       from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
       from .tokenization_canine import CanineTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_canine import (
                  CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
                  CanineForMultipleChoice,
                  CanineForQuestionAnswering,
                  CanineForSequenceClassification,
                  CanineForTokenClassification,
                  CanineLayer,
                  CanineModel,
                  CaninePreTrainedModel,
                  load_tf_weights_in_canine,
              )


else:
       import sys

       lowerCamelCase           =					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
