

import torch

from diffusers import StableDiffusionPipeline


__A :    Optional[int]      		=     '''path-to-your-trained-model'''
__A :    Any      		=     StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('''cuda''')

__A :    Dict      		=     '''A photo of sks dog in a bucket'''
__A :    int      		=     pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

image.save('''dog-bucket.png''')




import cmath
import math



def 				snake_case_(_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase			,	_UpperCamelCase					)							->     complex:



  """simple docstring"""






  _snake_case						=							math.radians(_UpperCamelCase					)
  _snake_case						=							math.radians(_UpperCamelCase					)

  # Convert voltage and current to rectangular form
  _snake_case						=							cmath.rect(_UpperCamelCase			,	_UpperCamelCase					)
  _snake_case						=							cmath.rect(_UpperCamelCase			,	_UpperCamelCase					)

  # Calculate apparent power
  return voltage_rect * current_rect


if __name__ == "__main__":
 import doctest

 doctest.testmod()

