





'''simple docstring'''







import unittest

import torch

from diffusers import DDIMScheduler, TextToVideoZeroPipeline
from diffusers.utils import load_pt, require_torch_gpu, slow

from ..test_pipelines_common import assert_mean_pixel_difference


@slow
@require_torch_gpu
class        __a   (unittest.TestCase  ):

							def      UpperCAmelCase__						(				self				:  Optional[int] )       ->							Optional[Any]:







													"""simple docstring"""
													UpperCAmelCase_      :   Optional[Any]      =	'''runwayml/stable-diffusion-v1-5'''
													UpperCAmelCase_      :   Any      =	TextToVideoZeroPipeline.from_pretrained(__magic_name__							,  torch_dtype=torch.floataa ).to('''cuda''' )
													UpperCAmelCase_      :   Any      =	DDIMScheduler.from_config(pipe.scheduler.config )
													UpperCAmelCase_      :   Optional[Any]      =	torch.Generator(device='''cuda''' ).manual_seed(0 )

													UpperCAmelCase_      :   Dict      =	'''A bear is playing a guitar on Times Square'''
													UpperCAmelCase_      :   List[Any]      =	pipe(prompt=__magic_name__							,  generator=__magic_name__ ).images

													UpperCAmelCase_      :   Any      =	load_pt(
													    '''https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main/text-to-video/A bear is playing a guitar on Times Square.pt''' )

													assert_mean_pixel_difference(__magic_name__							,  __magic_name__ )






'''simple docstring'''

from itertools import compress, repeat
from math import ceil, sqrt



def 				UpperCamelCase__      (      a__   ):


						'''simple docstring'''






						if num <= 2:
												return []
						if num == 3:
												return [2]

						# Odd sieve for numbers in range [3, num - 1]
						_lowerCAmelCase					    =bytearray(B'\x01'   ) * ((num >> 1) - 1)

						for i in range(3      ,   int(sqrt(a__   )   ) + 1      ,   2   ):
												if sieve[(i >> 1) - 1]:
																		_lowerCAmelCase					    =i**2
																		_lowerCAmelCase					    =repeat(
																		    0      ,   ceil((num - i_squared) / (i << 1)   )   )

						return [2] + list(compress(range(3      ,   a__      ,   2   )      ,   a__   )   )


if __name__ == "__main__":
							import doctest

							doctest.testmod()





