The proposed lightweight inference scheme can be extended to other forward-only training algorithms by adapting the confidence-based approach to the specific characteristics of each algorithm. For instance, if a different forward-only algorithm uses a similar concept of measuring goodness or confidence at each layer, the same principles can be applied. The key is to identify the appropriate metrics or indicators within the algorithm that can serve as proxies for confidence in the inference process. By customizing the lightweight scheme to the unique features of each algorithm, it can be effectively integrated to enhance computational efficiency in a variety of forward-only models.