 :].copy_(unet.conv_in.weight)
    unet.conv_in = new_conv_in These UNet parameters are updated by the optimizer:   Copied optimizer = optimizer_cls(
    unet.parameters(),
    lr=args.learning_rate,
    betas=(args.adam_beta1, args.adam_beta2),
    weight_decay=args.adam_weight_decay,
    eps=args.adam_epsilon,
) Next, the edited images and and edit instructions are preprocessed and tokenized. It is important the same image transformations are