



"""simple docstring"""

def       __magic_name__    (   _lowerCamelCase				: int					):






							if not isinstance(_UpperCamelCase  ,       _UpperCamelCase					):
														raise ValueError("""Input must be an integer"""					)
							if input_num <= 0:
														raise ValueError("""Input must be positive"""					)
							return sum(
							    divisor for divisor in range(1  ,       input_num // 2 + 1					) if input_num % divisor == 0					)


if __name__ == "__main__":
	import doctest

	doctest.testmod()





"""simple docstring"""

import torch

from diffusers import DiffusionPipeline




class SCREAMING_SNAKE_CASE__					(		__snake_case      ):



						def __init__(self						,     _lowercase						,     _lowercase							):





													'''simple docstring'''

													super().__init__()

													self.register_modules(unet=_lowercase						,     scheduler=_lowercase							)





						def __call__(self							):





													'''simple docstring'''

													__a		:		Dict									=       torch.randn(
													    (1, self.unet.config.in_channels, self.unet.config.sample_size, self.unet.config.sample_size)						,     )
													__a		:		Optional[Any]									=       1

													__a		:		List[str]									=       self.unet(_lowercase						,     _lowercase							).sample
													__a		:		Union[str, Any]									=       self.scheduler.step(_lowercase						,     _lowercase						,     _lowercase							).prev_sample

													__a		:		Optional[int]									=       scheduler_output - scheduler_output + torch.ones_like(_lowercase							)

													return result

