class UnetSchedulerOneForwardPipeline(DiffusionPipeline):
def __init__(self, unet, scheduler):
super().__init__()

self.register_modules(unet=unet, scheduler=scheduler)
```  
1. In the forward pass (which we recommend defining as `__call__`), you can add any feature you'd like. For the "one-step" pipeline, create a random image and call the UNet and scheduler once by setting `timestep=1`.  
```py
from diffusers import DiffusionPipeline
import torch