



'''simple docstring'''






import torch

from diffusers import StableDiffusionPipeline


lowerCAmelCase:      int		 =		'path-to-your-trained-model'
lowerCAmelCase:      str		 =		StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')

lowerCAmelCase:      int		 =		'A photo of sks dog in a bucket'
lowerCAmelCase:      Union[str, Any]		 =		pipe(prompt, num_inference_steps=5_0, guidance_scale=7.5).images[0]

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




'''simple docstring'''






from pathlib import Path

import fire
def    lowerCamelCase__ (		_A				,    _A				,    _A       ):
  a		:      Optional[Any]       =  Path(_A       )
  a		:      Tuple       =  Path(_A       )
  dest_dir.mkdir(exist_ok=_A       )
  for path in src_dir.iterdir():
    a		:      Tuple       =  [x.rstrip() for x in list(path.open().readlines()       )][:n]
    a		:      List[str]       =  dest_dir.joinpath(path.name       )
    print(_A       )
    dest_path.open('w'       ).write('\n'.join(_A       )       )


if __name__ == "__main__":
     fire.Fire(minify)