

import argparse

from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging


logging.set_verbosity_info()



def   __UpperCAmelCase					(      __a :     Dict						,__a :     List[str]						,__a :     int						,__a :     List[Any]      )     ->	str:

					"""simple docstring"""

					_a      :       Any   =						BigBirdConfig.from_json_file(__a      )
					print(F"""Building PyTorch model from configuration: {config}"""      )

					if is_trivia_qa:
										_a      :       Dict   =						BigBirdForQuestionAnswering(__a      )
					else:
										_a      :       Optional[int]   =						BigBirdForPreTraining(__a      )

					# Load weights from tf checkpoint
					load_tf_weights_in_big_bird(__a						,__a						,is_trivia_qa=__a      )

					# Save pytorch-model
					print(F"""Save PyTorch model to {pytorch_dump_path}"""      )
					model.save_pretrained(__a      )


if __name__ == "__main__":
			a__												=						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(
			    '''--big_bird_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.'''
			)
			parser.add_argument(
			    '''--is_trivia_qa''', action='''store_true''', help='''Whether to convert a model with a trivia_qa head.'''
			)
			a__												=						parser.parse_args()
			convert_tf_checkpoint_to_pytorch(
			    args.tf_checkpoint_path, args.big_bird_config_file, args.pytorch_dump_path, args.is_trivia_qa
			)










def    _A	(   lowerCamelCase ):
   a__						:    Optional[Any]   		=	1
   for i in range(1				,			num + 1 ):
      fact *= i
   return fact






def    _A	(   lowerCamelCase ):
   a__						:    List[Any]   		=	0
   while number > 0:
      a__						:    str   		=	number % 10
      sum_of_digits += last_digit
      a__						:    Dict   		=	number // 10  # Removing the last_digit from the given number
   return sum_of_digits






def    _A	(   lowerCamelCase = 100 ):
   a__						:    Any   		=	factorial(lowerCamelCase )
   a__						:    Optional[Any]   		=	split_and_add(lowerCamelCase )
   return result


if __name__ == "__main__":
  print(solution(int(input("""Enter the Number: """).strip())))

