

import math
from collections.abc import Iterator
from itertools import takewhile



def   __UpperCAmelCase					(      __a :     int      )     ->	bool:

					"""simple docstring"""

					if 1 < number < 4:
										# 2 and 3 are primes
										return True
					elif number < 2 or number % 2 == 0 or number % 3 == 0:
										# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
										return False

					# All primes number are in format of 6k +/- 1
					for i in range(5						,int(math.sqrt(__a      ) + 1      )						,6      ):
										if number % i == 0 or number % (i + 2) == 0:
															return False
					return True



def   __UpperCAmelCase					(      )     ->	Iterator[int]:

					"""simple docstring"""

					_a      :       Dict   =						2
					while True:
										if is_prime(__a      ):
															yield num
										num += 1



def   __UpperCAmelCase					(      __a :     int = 2_000_000      )     ->	int:

					"""simple docstring"""

					return sum(takewhile(lambda __a      : x < n						,prime_generator()      )      )


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







import numpy as np

from transformers import Pipeline





def 	_lowerCAmelCase					( UpperCamelCase__:  Optional[Any]    )			-> Optional[int]:





	"""simple docstring"""







	A             =					np.max(UpperCamelCase__				,       axis=-1				,       keepdims=UpperCamelCase__    )
	A             =					np.exp(outputs - maxes    )
	return shifted_exp / shifted_exp.sum(axis=-1				,       keepdims=UpperCamelCase__    )






class    _UpperCamelCase     (       __snake_case					):

				"""simple docstring"""







				def   _UpperCAmelCase       (    self					, **a__ )						->					Union[str, Any]:
					A             =					{}
					if "second_text" in kwargs:
						A             =					kwargs["""second_text"""]
					return preprocess_kwargs, {}, {}

				def   _UpperCAmelCase       (    self					, a__					, a__=None )						->					str:
					return self.tokenizer(a__					, text_pair=a__					, return_tensors=self.framework )

				def   _UpperCAmelCase       (    self					, a__ )						->					Tuple:
					return self.model(**a__ )

				def   _UpperCAmelCase       (    self					, a__ )						->					Optional[int]:
					A             =					model_outputs.logits[0].numpy()
					A             =					softmax(a__ )

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



