diffusers/main/en/api/models/stable_cascade_unet.md

# StableCascadeUNet

A UNet model from the [Stable Cascade pipeline](../pipelines/stable_cascade).

## StableCascadeUNet[[diffusers.models.StableCascadeUNet]]

- **sample** (`torch.Tensor`) -- The noisy input sample.
- **timestep_ratio** (`torch.Tensor`) --
  Timestep ratio used to compute the timestep embedding.
- **clip_text_pooled** (`torch.Tensor`) --
  Pooled CLIP text embeddings.
- **clip_text** (`torch.Tensor`, *optional*) --
  Sequence-level CLIP text embeddings.
- **clip_img** (`torch.Tensor`, *optional*) --
  CLIP image embeddings.
- **effnet** (`torch.Tensor`, *optional*) --
  EfficientNet feature map used as additional conditioning.
- **pixels** (`torch.Tensor`, *optional*) --
  Pixel-level conditioning tensor. If `None`, a tensor of zeros is used.
- **sca** (`torch.Tensor`, *optional*) --
  Optional `sca` conditioning value used to build the timestep embedding.
- **crp** (`torch.Tensor`, *optional*) --
  Optional `crp` conditioning value used to build the timestep embedding.
- **return_dict** (`bool`, *optional*, defaults to `True`) --
  Whether or not to return a `StableCascadeUNetOutput` instead of a plain tuple.