es: collate_fn(examples, args.with_prior_preservation),
    num_workers=args.dataloader_num_workers,
) Lastly, the training loop takes care of the remaining steps such as converting images to latent space, adding noise to the input, predicting the noise residual, and calculating the loss. If you want to learn more about how the training loop works, check out the Understanding pipelines, models and schedulers tutorial which breaks down the basic