





"""simple docstring"""



def 						__lowercase	(  snake_case_    :    int		)  ->int:



    '''simple docstring'''







    __A       :		str							=	1
    for i in range(1							,num + 1		):
        fact *= i
    return fact







def 						__lowercase	(  snake_case_    :    int		)  ->int:



    '''simple docstring'''







    __A       :		str							=	0
    while number > 0:
        __A       :		Optional[int]							=	number % 10
        sum_of_digits += last_digit
        __A       :		Dict							=	number // 10  # Removing the last_digit from the given number
    return sum_of_digits







def 						__lowercase	(  snake_case_    :    int = 100		)  ->int:



    '''simple docstring'''







    __A       :		Optional[int]							=	factorial(snake_case_		)
    __A       :		Optional[Any]							=	split_and_add(snake_case_		)
    return result


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











"""simple docstring"""



import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
       from transformers import AutoModelForSeqaSeqLM, AutoTokenizer






@require_torch
@require_sentencepiece
@require_tokenizers
class 						__snake_case   (						unittest.TestCase	):





 """simple docstring"""


 @slow
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     __A       :		Any							=	AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''   ,		return_dict=__lowerCamelCase    ).to(__lowerCamelCase    )
     __A       :		Optional[Any]							=	AutoTokenizer.from_pretrained('''google/mt5-small'''    )

     __A       :		Optional[int]							=	tokenizer('''Hello there'''   ,		return_tensors='''pt'''    ).input_ids
     __A       :		str							=	tokenizer('''Hi I am'''   ,		return_tensors='''pt'''    ).input_ids

     __A       :		Any							=	model(input_ids.to(__lowerCamelCase    )   ,		labels=labels.to(__lowerCamelCase    )    ).loss
     __A       :		Tuple							=	-(labels.shape[-1] * loss.item())

     __A       :		int							=	-8_4.9_1_2_7
     self.assertTrue(abs(mtf_score - EXPECTED_SCORE    ) < 1e-4    )




