



def      lowerCAmelCase_					(  _lowercase    :       str)							->	list:







			"""simple docstring"""
			a__       :						Union[str, Any]							=  [0] * len(_lowercase)

			for i in range(1						,       len(_lowercase)):
						# use last results for better performance - dynamic programming
						a__       :						Tuple							=  prefix_result[i - 1]
						while j > 0 and input_string[i] != input_string[j]:
									a__       :						Optional[int]							=  prefix_result[j - 1]

						if input_string[i] == input_string[j]:
									j += 1
						a__       :						Tuple							=  j

			return prefix_result

def      lowerCAmelCase_					(  _lowercase    :       str)							->	int:







			"""simple docstring"""
			return max(prefix_function(_lowercase))


if __name__ == "__main__":
		import doctest

		doctest.testmod()









import torch

from diffusers import StableDiffusionPipeline


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

_lowercase		:				Any      		="A photo of sks dog in a bucket"
_lowercase		:				Any      		=pipe(prompt, num_inference_steps=50, guidance_scale=7.5).images[0]

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




