





import argparse

import torch

from transformers import RoFormerConfig, RoFormerForMaskedLM, load_tf_weights_in_roformer
from transformers.utils import logging


logging.set_verbosity_info()

def     UpperCAmelCase_						(						_UpperCAmelCase       :Optional[Any]     ,	_UpperCAmelCase       :int     ,	_UpperCAmelCase       :str							)  ->							List[Any]:
     '''simple docstring'''


     A_					      =					RoFormerConfig.from_json_file(_A							)
     print(f'Building PyTorch model from configuration: {config}'							)
     A_					      =					RoFormerForMaskedLM(_A							)

     # Load weights from tf checkpoint
     load_tf_weights_in_roformer(_A     ,	_A     ,	_A							)

     # Save pytorch-model
     print(f'Save PyTorch model to {pytorch_dump_path}'							)
     torch.save(model.state_dict()     ,	_A     ,	_use_new_zipfile_serialization=_A							)


if __name__ == "__main__":
    a__			:    Optional[Any]			      =		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(
        '--bert_config_file',
        default=None,
        type=str,
        required=True,
        help=(
            'The config json file corresponding to the pre-trained BERT model. \n'
            'This 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.bert_config_file, args.pytorch_dump_path)










import itertools
from pathlib import Path

def     UpperCAmelCase_						(						_UpperCAmelCase       :list[str]							)  ->							int:
     '''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     UpperCAmelCase_						(						_UpperCAmelCase       :str = "keylog.txt"							)  ->							int:
     '''simple docstring'''


     A_					      =					Path(_UpperCAmelCase							).parent.joinpath(_UpperCAmelCase							).read_text().splitlines()

     return find_secret_passcode(_UpperCAmelCase							)


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



