


'''simple docstring'''
import math







def       a_				(	UpperCamelCase_ ):
							A_			    =		[]
							A_			    =		2
							A_			    =		int(math.sqrt(UpperCamelCase_ ) )  # Size of every segment
							A_			    =		[True] * (end + 1)
							A_			    =		[]

							while start <= end:
														if temp[start] is True:
																					in_prime.append(UpperCamelCase_ )
																					for i in range(start * start						,  end + 1						,  UpperCamelCase_ ):
																												A_			    =		False
														start += 1
							prime += in_prime

							A_			    =		end + 1
							A_			    =		min(2 * end						,  UpperCamelCase_ )

							while low <= n:
														A_			    =		[True] * (high - low + 1)
														for each in in_prime:
																					A_			    =		math.floor(low / each ) * each
																					if t < low:
																												t += each

																					for j in range(UpperCamelCase_						,  high + 1						,  UpperCamelCase_ ):
																												A_			    =		False

														for j in range(len(UpperCamelCase_ ) ):
																					if temp[j] is True:
																												prime.append(j + low )

														A_			    =		high + 1
														A_			    =		min(high + end						,  UpperCamelCase_ )

							return prime







print(sieve(10**6))












"""simple docstring"""


from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
		from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline



