






'''simple docstring'''

import argparse

import torch

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


logging.set_verbosity_info()






def 	_UpperCAmelCase    (  a		:	int						,			a		:	Optional[Any]						,			a		:	Optional[Any]							)			->			List[Any]:





						"""simple docstring"""
						lowercase_      :   Optional[Any]        =			LxmertConfig.from_json_file(lowercase__							)
						print(f"Building PyTorch model from configuration: {config}"							)
						lowercase_      :   Union[str, Any]        =			LxmertForPreTraining(lowercase__							)

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

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


if __name__ == "__main__":
		A:      List[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(
		    "--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."
		)
		A:      Any  				=				parser.parse_args()
		convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)








'''simple docstring'''

def 	_UpperCAmelCase    (  a		:	int						,			a		:	int							)			->			int:





						"""simple docstring"""
						while second != 0:
												lowercase_      :   Any        =			first & second
												first ^= second
												lowercase_      :   List[str]        =			c << 1
						return first


if __name__ == "__main__":
						import doctest

						doctest.testmod()

						A:      Union[str, Any]  				=				int(input("Enter the first number: ").strip())
						A:      Union[str, Any]  				=				int(input("Enter the second number: ").strip())
						print(f"""{add(first, second) = }""")
