When defining neural network architectures such as residual blocks, frameworks like MXNet allow developers to build components based on hybrid classes (e.g., HybridBlock). While this approach may slightly alter standard imperative implementations, it is deliberately utilized to improve computational efficiency during execution by enabling graph compilation.