finetune_instruct_pix2pix.py [795:812]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        input_ids = torch.stack([example["input_ids"] for example in examples])
        return {
            "original_pixel_values": original_pixel_values,
            "edited_pixel_values": edited_pixel_values,
            "input_ids": input_ids,
        }

    # DataLoaders creation:
    train_dataloader = torch.utils.data.DataLoader(
        train_dataset,
        shuffle=True,
        collate_fn=collate_fn,
        batch_size=args.train_batch_size,
        num_workers=args.dataloader_num_workers,
    )

    # Scheduler and math around the number of training steps.
    overrode_max_train_steps = False
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -



train_instruct_pix2pix.py [692:709]:
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
        input_ids = torch.stack([example["input_ids"] for example in examples])
        return {
            "original_pixel_values": original_pixel_values,
            "edited_pixel_values": edited_pixel_values,
            "input_ids": input_ids,
        }

    # DataLoaders creation:
    train_dataloader = torch.utils.data.DataLoader(
        train_dataset,
        shuffle=True,
        collate_fn=collate_fn,
        batch_size=args.train_batch_size,
        num_workers=args.dataloader_num_workers,
    )

    # Scheduler and math around the number of training steps.
    overrode_max_train_steps = False
- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -