maisi unconditioned inference return noise

Hallo,

I tried longer to make the diffusion unet (rectified flow version) work but without success. the VAE performes correct and encoding and reconstruction look fine. I take all the configs from the repo so configuration as well as weights are equivalently loaded as in https://github.com/Project-MONAI/tutorials/blob/main/generation/maisi/maisi_inference_tutorial.ipynb.

Using the diffusion unet with the existing code of diffusion_model_infer.py with

from scripts.diff_model_infer import run_inference
data = run_inference(
  args,
  device,
  autoencoder,
  diffusion_unet,
  1.4,#scale_factor,
  None,#top_region_index_tensor,
  None, #bottom_region_index_tensor,
  torch.tensor([[1.5,1.5,4.0]]).to('cuda'),#spacing_tensor,
  torch.tensor([1]).to('cuda'),#modality_tensor,
  (96,96,96),#output_size,
  4,
  logger,
)

I saw that there was an issue with the architecture which was different during training and the implementation but I'm not sure if that is related.
https://github.com/Project-MONAI/MONAI/issues/7991.
Some observations I made is when I would like to just reconstruction an image and basically make one step, the recon get's extremly noise.

For any suggestion what could be the potential issue, I'm thankful.

Best,
Lukas

从 scripts/diff_model_infer.py 和 MAISI inference tutorial notebook 开始，复现会产生噪声的单步重建。将推理架构和加载的配置与训练实现进行比较，包括 issue 7991 中讨论的差异。当在所提供的设置下，无条件推理或重建不再返回带噪输出时，即表示完成。