mage, depth_image], rows=1, cols=2) Load a ControlNet model conditioned on depth maps and the AutoPipelineForImage2Image:   Copied from diffusers import ControlNetModel, AutoPipelineForImage2Image
import torch

controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11f1p_sd15_depth", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
pipeline = AutoPipelineForImage2Image.from_pretrained(
    "runwayml/stable-diffusion-v