




import argparse

import torch

from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging


logging.set_verbosity_info()






def    snake_case(							__magic_name__					,						__magic_name__					,						__magic_name__       )					->				Optional[Any]:





     '''simple docstring'''


     lowercase   :  Dict        =					LxmertConfig.from_json_file(_UpperCAmelCase       )
     print(F"""Building PyTorch model from configuration: {config}"""       )
     lowercase   :  Union[str, Any]        =					LxmertForPreTraining(_UpperCAmelCase       )

     # Load weights from tf checkpoint
     load_tf_weights_in_lxmert(_UpperCAmelCase					,						_UpperCAmelCase					,						_UpperCAmelCase       )

     # Save pytorch-model
     print(F"""Save PyTorch model to {pytorch_dump_path}"""       )
     torch.save(model.state_dict()					,						_UpperCAmelCase       )


if __name__ == "__main__":
 lowerCAmelCase_						 =					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 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.'
 )
 lowerCAmelCase_						 =					parser.parse_args()
 convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)

def 		UpperCamelCase     (       _UpperCAmelCase  :   str  )   ->			bool:






						'''simple docstring'''

						_lowercase       :	List[str]           =   [int(_UpperCAmelCase  ) for i in ip_va_address.split("."  ) if i.isdigit()]
						return len(_UpperCAmelCase  ) == 4 and all(0 <= int(_UpperCAmelCase  ) <= 254 for octet in octets  )


if __name__ == "__main__":
							UpperCamelCase_						:     Dict	       =							input().strip()
							UpperCamelCase_						:     List[Any]	       =							"""valid""" if is_ip_va_address_valid(ip) else """invalid"""
							print(f'''{ip} is a {valid_or_invalid} IP v4 address.''')




