


from __future__ import annotations

import math




def 	A_ (							snake_case							:   List[str] )      ->    list[int]:



						'''simple docstring'''

						if num <= 0:
												__UpperCamelCase       =			f"{num}: Invalid input, please enter a positive integer."
												raise ValueError(snake_case )

						__UpperCamelCase       =			[True] * (num + 1)
						__UpperCamelCase       =			[]
						__UpperCamelCase       =			2
						__UpperCamelCase       =			int(math.sqrt(snake_case ) )

						while start <= end:
												# If start is a prime
												if sieve[start] is True:
																		prime.append(snake_case )

																		# Set multiples of start be False
																		for i in range(start * start ,      num + 1 ,      snake_case ):
																								if sieve[i] is True:
																														__UpperCamelCase       =			False

												start += 1

						for j in range(end + 1 ,      num + 1 ):
												if sieve[j] is True:
																		prime.append(snake_case )

						return prime


if __name__ == "__main__":
				print(prime_sieve(int(input("Enter a positive integer: ").strip())))






import unittest

from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax

from .test_modeling_common_flax import FlaxModelTesterMixin


if is_flax_available():
				import jax






@require_flax
class        SCREAMING_SNAKE_CASE__    (							SCREAMING_SNAKE_CASE_   ,		unittest.TestCase    ):

							"""simple docstring"""






							_snake_case     		=  FlaxAutoencoderKL



							@property
							def     A__		(  self			)->   int:





													'''simple docstring'''






													__UpperCamelCase       =			4
													__UpperCamelCase       =			3
													__UpperCamelCase       =			(32, 32)

													__UpperCamelCase       =			jax.random.PRNGKey(0			)
													__UpperCamelCase       =			jax.random.uniform(SCREAMING_SNAKE_CASE_     ,	((batch_size, num_channels) + sizes)			)

													return {"sample": image, "prng_key": prng_key}



							def     A__		(  self			)->   List[Any]:





													'''simple docstring'''






													__UpperCamelCase       =			{
													    '''block_out_channels''': [32, 64],
													    '''in_channels''': 3,
													    '''out_channels''': 3,
													    '''down_block_types''': ['''DownEncoderBlock2D''', '''DownEncoderBlock2D'''],
													    '''up_block_types''': ['''UpDecoderBlock2D''', '''UpDecoderBlock2D'''],
													    '''latent_channels''': 4,
													}
													__UpperCamelCase       =			self.dummy_input
													return init_dict, inputs_dict




