






"""simple docstring"""

import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
			import torch

			from transformers.generation import DisjunctiveConstraint

@require_torch
class 						A_							(      unittest.TestCase  ):







				def     _snake_case					(							self							:						Optional[Any]	)				->					List[Any]:
										# For consistency across different places the DisjunctiveConstraint is called,
										# dc.token_ids is a list of integers. It is also initialized only by integers.

										__magic_name__            =     [[1, 2, 4], [1, 2, 3, 4]]
										__magic_name__            =     DisjunctiveConstraint(__lowerCamelCase	)
										self.assertTrue(isinstance(dc.token_ids						,    __lowerCamelCase	)	)

										with self.assertRaises(__lowerCamelCase	):
																DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]	)	)

										with self.assertRaises(__lowerCamelCase	):
																DisjunctiveConstraint([torch.LongTensor([1, 2, 4]	), torch.LongTensor([1, 2, 3, 4, 5]	)]	)







				def     _snake_case					(							self							:						Optional[int]	)				->					Dict:
										# We can't have constraints that are complete subsets of another. This leads to a preverse
										# interpretation of "constraint fulfillment": does generating [1,2,3] fulfill the constraint?
										# It would mean that it generated [1,2] which fulfills it, but it's in the middle of potentially
										# fulfilling [1,2,3,4]. If we believe that [1,2,3] does fulfill the constraint, then the algorithm
										# will necessarily never reach [1,2,3,4], giving users a false sense of control (better to just not allow it).
										__magic_name__            =     [[1, 2], [1, 2, 3, 4]]

										with self.assertRaises(__lowerCamelCase	):
																DisjunctiveConstraint(__lowerCamelCase	)  # fails here







				def     _snake_case					(							self							:						Optional[int]	)				->					Tuple:
										__magic_name__            =     [[1, 2, 3], [1, 2, 4]]

										__magic_name__            =     DisjunctiveConstraint(__lowerCamelCase	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(1	)
										__magic_name__            =     stepped is True and completed is False and reset is False
										self.assertTrue(__lowerCamelCase	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.current_seq == [1]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(2	)
										__magic_name__            =     stepped is True and completed is False and reset is False
										self.assertTrue(__lowerCamelCase	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.current_seq == [1, 2]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(3	)
										__magic_name__            =     stepped is True and completed is True and reset is False
										self.assertTrue(__lowerCamelCase	)
										self.assertTrue(dc.completed	)  # Completed!
										self.assertTrue(dc.current_seq == [1, 2, 3]	)







				def     _snake_case					(							self							:						Dict	)				->					Tuple:
										__magic_name__            =     [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

										__magic_name__            =     DisjunctiveConstraint(__lowerCamelCase	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(1	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.current_seq == [1]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(2	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.current_seq == [1, 2]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(4	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.current_seq == [1, 2, 4]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(5	)
										self.assertTrue(dc.completed	)  # Completed!
										self.assertTrue(dc.current_seq == [1, 2, 4, 5]	)

										dc.reset()

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(1	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.remaining() == 3	)
										self.assertTrue(dc.current_seq == [1]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(2	)
										self.assertTrue(not dc.completed	)
										self.assertTrue(dc.remaining() == 2	)
										self.assertTrue(dc.current_seq == [1, 2]	)

										__magic_name__      ,    __magic_name__      ,    __magic_name__            =     dc.update(5	)
										self.assertTrue(dc.completed	)  # Completed!
										self.assertTrue(dc.remaining() == 0	)
										self.assertTrue(dc.current_seq == [1, 2, 5]	)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:int = 2_0_0_0_0_0_0   ):

						'''simple docstring'''






						__magic_name__            =     [0 for i in range(n + 1   )]
						__magic_name__            =     1
						__magic_name__            =     1

						for i in range(2 ,						int(n**0.5   ) + 1   ):
												if primality_list[i] == 0:
																		for j in range(i * i ,						n + 1 ,						__lowerCamelCase   ):
																								__magic_name__            =     1
						__magic_name__            =     0
						for i in range(__lowerCamelCase   ):
												if primality_list[i] == 0:
																		sum_of_primes += i
						return sum_of_primes


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



