'''simple docstring'''
import argparse

from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging


logging.set_verbosity_info()







def 							__UpperCamelCase   (				__UpperCAmelCase     :				List[str]   ,      __UpperCAmelCase     :				List[Any]   ,      __UpperCAmelCase     :				Dict )       ->  List[str]:
  # Initialise PyTorch model
  lowercase							:       str											=      TaConfig.from_json_file(__UpperCAmelCase )
  print(f"""Building PyTorch model from configuration: {config}""" )
  lowercase							:       Tuple											=      TaForConditionalGeneration(__UpperCAmelCase )

  # Load weights from tf checkpoint
  load_tf_weights_in_ta(__UpperCAmelCase   ,      __UpperCAmelCase   ,      __UpperCAmelCase )

  # Save pytorch-model
  print(f"""Save PyTorch model to {pytorch_dump_path}""" )
  model.save_pretrained(__UpperCAmelCase )


if __name__ == "__main__":
 _A		:			List[str]	      =argparse.ArgumentParser()
 # Required parameters
 parser.add_argument(
     '''--tf_checkpoint_path''', default=None, type=str, required=True, help='''Path to the TensorFlow checkpoint path.'''
 )
 parser.add_argument(
     '''--config_file''',
     default=None,
     type=str,
     required=True,
     help=(
         '''The config json file corresponding to the pre-trained T5 model. \nThis specifies the model architecture.'''
     ),
 )
 parser.add_argument(
     '''--pytorch_dump_path''', default=None, type=str, required=True, help='''Path to the output PyTorch model.'''
 )
 _A		:			Tuple	      =parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)
'''simple docstring'''
import itertools
from pathlib import Path







def 							__UpperCamelCase   (				__UpperCAmelCase     :				list[str] )       ->  int:
  lowercase							:       List[str]											=      [tuple(__UpperCAmelCase ) for login in logins]

  lowercase							:       List[Any]											=      {char for login in split_logins for char in login}

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

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

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







def 							__UpperCamelCase   (				__UpperCAmelCase     :				str = "keylog.txt" )       ->  int:
  lowercase							:       Union[str, Any]											=      Path(__UpperCAmelCase ).parent.joinpath(__UpperCAmelCase ).read_text().splitlines()

  return find_secret_passcode(__UpperCAmelCase )


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