


'''simple docstring'''

def 							__magic_name__(						lowerCamelCase):
						__lowerCAmelCase							       =				0
						while num > 0:
												digit_sum += num % 1_0
												num //= 1_0
						return digit_sum

def 							__magic_name__(						lowerCamelCase = 1_0_0):
						__lowerCAmelCase							       =				1
						__lowerCAmelCase							       =				2

						for i in range(2,				max_n + 1):
												__lowerCAmelCase							       =				pre_numerator
												__lowerCAmelCase							       =				2 * i // 3 if i % 3 == 0 else 1
												__lowerCAmelCase							       =				cur_numerator
												__lowerCAmelCase							       =				e_cont * pre_numerator + temp

						return sum_digits(lowerCamelCase)


if __name__ == "__main__":
	print(f"""{solution() = }""")







'''simple docstring'''

import numpy as np

from transformers import Pipeline

def 							__magic_name__(						lowerCamelCase):
						__lowerCAmelCase							       =				np.max(lowerCamelCase,				axis=-1,				keepdims=lowerCamelCase)
						__lowerCAmelCase							       =				np.exp(outputs - maxes)
						return shifted_exp / shifted_exp.sum(axis=-1,				keepdims=lowerCamelCase)




class       a__				( __A      ):







				"""simple docstring"""



				def 					_snake_case  (self       ,			**__lowercase		):
										__lowerCAmelCase							       =				{}
										if "second_text" in kwargs:
																__lowerCAmelCase							       =				kwargs['''second_text''']
										return preprocess_kwargs, {}, {}




				def 					_snake_case  (self       ,			__lowercase       ,			__lowercase=None		):
										return self.tokenizer(__lowercase       ,			text_pair=__lowercase       ,			return_tensors=self.framework		)




				def 					_snake_case  (self       ,			__lowercase		):
										return self.model(**__lowercase		)




				def 					_snake_case  (self       ,			__lowercase		):
										__lowerCAmelCase							       =				model_outputs.logits[0].numpy()
										__lowerCAmelCase							       =				softmax(__lowercase		)

										__lowerCAmelCase							       =				np.argmax(__lowercase		)
										__lowerCAmelCase							       =				self.model.config.idalabel[best_class]
										__lowerCAmelCase							       =				probabilities[best_class].item()
										__lowerCAmelCase							       =				logits.tolist()
										return {"label": label, "score": score, "logits": logits}

