


"""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 _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			LxmertConfig.from_json_file(_UpperCamelCase      )
			print(f"Building PyTorch model from configuration: {config}"      )
			__lowerCAmelCase				    =			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__":
	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(
	    "--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     :   int			    =			parser.parse_args()
	convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.config_file, args.pytorch_dump_path)








"""simple docstring"""


def _lowerCamelCase	(		_UpperCamelCase      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			False
			while is_sorted is False:  # Until all the indices are traversed keep looping
						__lowerCAmelCase				    =			True
						for i in range(0    , len(_UpperCamelCase      ) - 1    , 2      ):  # iterating over all even indices
									if input_list[i] > input_list[i + 1]:
												__lowerCAmelCase    ,	__lowerCAmelCase				    =			input_list[i + 1], input_list[i]
												# swapping if elements not in order
												__lowerCAmelCase				    =			False

						for i in range(1    , len(_UpperCamelCase      ) - 1    , 2      ):  # iterating over all odd indices
									if input_list[i] > input_list[i + 1]:
												__lowerCAmelCase    ,	__lowerCAmelCase				    =			input_list[i + 1], input_list[i]
												# swapping if elements not in order
												__lowerCAmelCase				    =			False
			return input_list


if __name__ == "__main__":
	print("Enter list to be sorted")
	A     :   Union[str, Any]			    =			[int(x) for x in input().split()]
	# inputing elements of the list in one line
	A     :   str			    =			odd_even_sort(input_list)
	print("The sorted list is")
	print(sorted_list)




