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import torch
from PIL.Image import Image
from diffusers import StableDiffusionXLPipeline
from pipelines.models import TextToImageRequest
from torch import Generator
from onediffx import compile_pipe, load_pipe
def load_pipeline() -> StableDiffusionXLPipeline:
pipeline = StableDiffusionXLPipeline.from_pretrained(
"./models/newdream-sdxl-20",
torch_dtype=torch.float16,
local_files_only=True,
).to("cuda")
pipeline = compile_pipe(pipeline)
load_pipe(pipeline, dir="models/poo2")
for _ in range(4):
pipeline(prompt="kamala harris", num_inference_steps=20)
return pipeline
def infer(request: TextToImageRequest, pipeline: StableDiffusionXLPipeline) -> Image:
if request.seed is None:
generator = None
else:
generator = Generator(pipeline.device).manual_seed(request.seed)
return pipeline(
prompt=request.prompt,
negative_prompt=request.negative_prompt,
width=request.width,
height=request.height,
generator=generator,
end_cfg=0.5,
num_inference_steps=20,
).images[0]
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