r parameters:   Copied params_to_optimize = t2iadapter.parameters()
optimizer = optimizer_class(
    params_to_optimize,
    lr=args.learning_rate,
    betas=(args.adam_beta1, args.adam_beta2),
    weight_decay=args.adam_weight_decay,
    eps=args.adam_epsilon,
) Lastly, in the training loop, the adapter conditioning image and the text embeddings are passed to the UNet to predict the noise residual:   Copied t2iadapter_image = batch["conditioni