• 在 192x256 分辨率下运行，仅需额外 +0.6GB 内存
• 在 320x320 分辨率下运行，仅需额外 +1GB 内存

from diffusers import StableDiffusionOnnxPipeline
import torch
from diffusers import (
DDPMScheduler,
DDIMScheduler,
PNDMScheduler,
LMSDiscreteScheduler,
EulerDiscreteScheduler,
EulerAncestralDiscreteScheduler,
DPMSolverMultistepScheduler
)

scheduler = DPMSolverMultistepScheduler.from_pretrained(\"./model\", subfolder=\"scheduler\")

pipe = StableDiffusionOnnxPipeline.from_pretrained(
'./model',
custom_pipeline=\"lpw_stable_diffusion_onnx\",
revision=\"onnx\",
scheduler=scheduler,
safety_checker=None,
provider=\"CPUExecutionProvider\"
)


prompt = \"a photo of \"
neg_prompt = \"\"

generator = torch.Generator(device=\"cpu").manual_seed(1)


image = pipe.text2img(prompt,negative_prompt=neg_prompt, num_inference_steps=8, width=192, height=256, guidance_scale=10, generator=generator, max_embeddings_multiples=3).images[0]
image.save('./test.png')