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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) | |
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 | |