import argparse

import torch

from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging


logging.set_verbosity_info()



def lowerCamelCase  (   SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE  ,			SCREAMING_SNAKE_CASE	):
    '''simple docstring'''







    __UpperCamelCase     :int			  =		RemBertConfig.from_json_file(__snake_case	)
    print('''Building PyTorch model from configuration: {}'''.format(str(__snake_case	)	)	)
    __UpperCamelCase     :Dict			  =		RemBertModel(__snake_case	)

    # Load weights from tf checkpoint
    load_tf_weights_in_rembert(__snake_case  ,			__snake_case  ,			__snake_case	)

    # Save pytorch-model
    print('''Save PyTorch model to {}'''.format(__snake_case	)	)
    torch.save(model.state_dict()  ,			__snake_case	)


if __name__ == "__main__":
    __lowercase							 =					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(
        '''--rembert_config_file''',
        default=None,
        type=str,
        required=True,
        help=(
            '''The config json file corresponding to the pre-trained RemBERT 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.'''
    )
    __lowercase							 =					parser.parse_args()
    convert_rembert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.rembert_config_file, args.pytorch_dump_path)







"""simple docstring"""





def       lowerCamelCase__		(			__snake_case = 10_00	)							->		int:


					"""simple docstring"""





					_UpperCamelCase							 =  2**power
					_UpperCamelCase							 =  str(__snake_case	)
					_UpperCamelCase							 =  list(__snake_case	)
					_UpperCamelCase							 =  0

					for i in list_num:
										sum_of_num += int(__snake_case	)

					return sum_of_num


if __name__ == "__main__":
				_a														=		int(input("""Enter the power of 2: """).strip())
				print("""2 ^ """, power, """ = """, 2**power)
				_a														=		solution(power)
				print("""Sum of the digits is: """, result)






