ptimizer is set up to update the ControlNet parameters:   Copied params_to_optimize = controlnet.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,
) Finally, in the training loop, the conditioning text embeddings and image are passed to the down and mid-blocks of the ControlNet model:   Cop