diffusers/tools

1#!/usr/bin/env python32from diffusers import DPMSolverMultistepScheduler, StableDiffusionXLPipeline, DPMSolverSDEScheduler3import hf_image_uploader as hiu4import torch5 6path = "stabilityai/stable-diffusion-xl-base-1.0"7vae_path = "madebyollin/sdxl-vae-fp16-fix"8 9# vae = AutoencoderKL.from_pretrained(vae_path, torch_dtype=torch.float16)10# pipe = StableDiffusionXLPipeline.from_pretrained(path, torch_dtype=torch.float16, vae=vae, variant="fp16", use_safetensors=True, local_files_only=True, add_watermarker=False)11pipe = StableDiffusionXLPipeline.from_pretrained(path, torch_dtype=torch.float16, variant="fp16", use_safetensors=True)12pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config, algorithm_type="sde-dpmsolver++")13pipe.to("cuda")14 15prompt = "An astronaut riding a green horse on Mars"16steps = 2017 18for i in range(2):19    width = 512 * (i + 1)20    height = 512 * (i + 1)21    image = pipe(prompt=prompt, width=width, height=height, num_inference_steps=steps).images[0]22    hiu.upload(image, "patrickvonplaten/images")23 24pipe.scheduler = DPMSolverSDEScheduler.from_config(pipe.scheduler.config, algorithm_type="sde-dpmsolver++")25 26for i in range(2):27    width = 512 * (i + 1)28    height = 512 * (i + 1)29    image = pipe(prompt=prompt, width=width, height=height, num_inference_steps=steps).images[0]30    hiu.upload(image, "patrickvonplaten/images")31