* `layers_per_block`: the number of ResNet blocks present in each UNet block.  
To use the model for inference, create the image shape with random Gaussian noise. It should have a `batch` axis because the model can receive multiple random noises, a `channel` axis corresponding to the number of input channels, and a `sample_size` axis for the height and width of the image:  
```py
>>> import torch