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noise image -> -------------
              |             |----> cleared image
step (int) -> |  denoiser   |
              |             |
              --------------|
```The charm of deep learning lies in the fact that once a new task achieves improved performance with a certain architecture, many other tasks can refer to this architecture and benefit from it.

I believe the diffusion model is a typical example. Although I do not conduct research on diffusion models and currently have no related projects, there is no harm in understanding this network architecture.

The diffusion model is one that benefits from the image processing process.

By learning the reverse process of adding noise to images, the diffusion model acquires the ability to generate images from noise.

![noise-dog](noise-dog.png)

To enable the model to achieve better performance, the denoising step of the model is included as one of the inputs.