import torch from diffusers import StableDiffusionPipeline, EulerDiscreteScheduler, DPMSolverMultistepScheduler, \ OnnxStableDiffusionPipeline import pipeline_openvino_stable_diffusion from optimum.intel.openvino import OVStableDiffusionPipeline def get_sd_21(): model_id = "stabilityai/stable-diffusion-2-1-base" scheduler = EulerDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler") if torch.cuda.is_available(): pipe = StableDiffusionPipeline.from_pretrained( model_id, scheduler=scheduler, # safety_checker=None, revision="fp16", torch_dtype=torch.float16) pipe = pipe.to('cuda') else: pipe = StableDiffusionPipeline.from_pretrained( model_id, scheduler=scheduler, # safety_checker=None, revision="fp16", torch_dtype=torch.float16) return pipe def get_sd_every(): model_id = 'OFA-Sys/small-stable-diffusion-v0' scheduler = DPMSolverMultistepScheduler.from_pretrained(model_id, subfolder="scheduler") pipe = OVStableDiffusionPipeline.from_pretrained("OpenVINO/stable-diffusion-2-1-quantized", compile=False) pipe.compile() return pipe def get_sd_small(): pipe = OVStableDiffusionPipeline.from_pretrained("OpenVINO/stable-diffusion-2-1-quantized", compile=False) pipe.reshape(batch_size=1, height=256, width=256, num_images_per_prompt=1) pipe.compile() return pipe def get_sd_tiny(): pipe = OVStableDiffusionPipeline.from_pretrained("OpenVINO/stable-diffusion-2-1-quantized", compile=False) pipe.reshape(batch_size=1, height=512, width=512, num_images_per_prompt=1) pipe.compile() return pipe