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#!/usr/bin/env python3
from diffusers import DiffusionPipeline, EulerAncestralDiscreteScheduler
import torch
path = "runwayml/stable-diffusion-v1-5"
run_compile = False # Set True / False
use_karras_sigmas = False
pipe = DiffusionPipeline.from_pretrained(path, torch_dtype=torch.float16)
pipe = pipe.to("cuda")
pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config, use_karras_sigmas=use_karras_sigmas)
pipe.unet.to(memory_format=torch.channels_last)
if run_compile:
print("Run torch compile")
pipe.unet = torch.compile(pipe.unet, mode="reduce-overhead", fullgraph=True)
prompt = "ghibli style, a fantasy landscape with castles"
for _ in range(3):
images = pipe(prompt=prompt).images
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