nfig)
unet.load_state_dict(teacher_unet.state_dict(), strict=False)
unet.train() Now you can create the optimizer to update the UNet parameters:   Copied optimizer = optimizer_class(
    unet.parameters(),
    lr=args.learning_rate,
    betas=(args.adam_beta1, args.adam_beta2),
    weight_decay=args.adam_weight_decay,
    eps=args.adam_epsilon,
) Create the dataset:   Copied dataset = Text2ImageDataset(
    train_shards_path_or_url=args.train_s