diffusers/tools

1#!/usr/bin/env python32import torch3import numpy as np4from diffusers import StableDiffusionXLPipeline5 6path = "hf-internal-testing/tiny-stable-diffusion-xl-pipe"7 8pipe = StableDiffusionXLPipeline.from_pretrained(path)9pipe.unet.set_default_attn_processor()10 11prompt = "An astronaut riding a green horse on Mars"12steps = 313 14batch_size, height, width, ch = 1, 32, 32, 415num_elems = batch_size * height * width * ch16latents = (torch.arange(num_elems) / num_elems)[:, None, None, None].reshape(batch_size, ch, width, height)17print("latents", latents.abs().sum())18 19image = pipe(prompt, latents=latents, num_inference_steps=3, output_type="np", guidance_scale=7.5).images[0]20 21print(np.abs(image).sum())22