






"""simple docstring"""


from typing import TYPE_CHECKING

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


lowercase_    					=					{
    'configuration_esm': ['ESM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'EsmConfig'],
    'tokenization_esm': ['EsmTokenizer'],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_    					=					[
           'ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'EsmForMaskedLM',
           'EsmForSequenceClassification',
           'EsmForTokenClassification',
           'EsmModel',
           'EsmPreTrainedModel',
       ]
       lowercase_    					=					['EsmForProteinFolding', 'EsmFoldPreTrainedModel']

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_    					=					[
           'TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST',
           'TFEsmForMaskedLM',
           'TFEsmForSequenceClassification',
           'TFEsmForTokenClassification',
           'TFEsmModel',
           'TFEsmPreTrainedModel',
       ]

if TYPE_CHECKING:
       from .configuration_esm import ESM_PRETRAINED_CONFIG_ARCHIVE_MAP, EsmConfig
       from .tokenization_esm import EsmTokenizer

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_esm import (
                  ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  EsmForMaskedLM,
                  EsmForSequenceClassification,
                  EsmForTokenClassification,
                  EsmModel,
                  EsmPreTrainedModel,
              )
              from .modeling_esmfold import EsmFoldPreTrainedModel, EsmForProteinFolding

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_esm import (
                  TF_ESM_PRETRAINED_MODEL_ARCHIVE_LIST,
                  TFEsmForMaskedLM,
                  TFEsmForSequenceClassification,
                  TFEsmForTokenClassification,
                  TFEsmModel,
                  TFEsmPreTrainedModel,
              )


else:
       import sys

       lowercase_    					=					_LazyModule(__name__, globals()['__file__'], _import_structure)












"""simple docstring"""


import itertools
from pathlib import Path



def  lowerCAmelCase    (   __UpperCamelCase			):




  """simple docstring"""







  __A						      =			[tuple(__UpperCamelCase			) for login in logins]

  __A						      =			{char for login in split_logins for char in login}

  for permutation in itertools.permutations(__UpperCamelCase			):
    __A						      =			True
    for login in logins:
      if not (
          permutation.index(login[0]			)
          < permutation.index(login[1]			)
          < permutation.index(login[2]			)
      ):
        __A						      =			False
        break

    if satisfied:
      return int(''''''.join(__UpperCamelCase			)			)

  raise Exception('''Unable to find the secret passcode'''			)



def  lowerCAmelCase    (   __UpperCamelCase = "keylog.txt"			):




  """simple docstring"""







  __A						      =			Path(__UpperCamelCase			).parent.joinpath(__UpperCamelCase			).read_text().splitlines()

  return find_secret_passcode(__UpperCamelCase			)


if __name__ == "__main__":
       print(F'''{solution() = }''')




