


import torch

from diffusers import StableDiffusionPipeline


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

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

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






def       _a			(				SCREAMING_SNAKE_CASE						,    SCREAMING_SNAKE_CASE					):


		"""simple docstring"""




		lowercase__						=				len(SCREAMING_SNAKE_CASE					)
		lowercase__						=				[]
		for i in range(len(SCREAMING_SNAKE_CASE					) - pat_len + 1					):
				lowercase__						=				True
				for j in range(SCREAMING_SNAKE_CASE					):
						if s[i + j] != pattern[j]:
								lowercase__						=				False
								break
				if match_found:
						position.append(SCREAMING_SNAKE_CASE					)
		return position


if __name__ == "__main__":
			assert naive_pattern_search('ABCDEFG', 'DE') == [3]
			print(naive_pattern_search('ABAAABCDBBABCDDEBCABC', 'ABC'))


