print(np.abs(image).sum())
```  
Running the code above prints one value, but if you run it again you get a different value.  
Each time the pipeline is run, [torch.randn](https://pytorch.org/docs/stable/generated/torch.randn.html) uses a different random seed to create the Gaussian noise tensors. This leads to a different result each time it is run and enables the diffusion pipeline to generate a different random image each time.