[D] Using clean architecture and DDD in machine learning | deep learning projects

Basically, the title. Has anyone used principles of clean architecture and DDD to build a deep learning or machine learning solution? If so, how do you code domains? Do you introduce frameworks like PyTorch right into the domain and application layers? Or do you try to write abstractions for training processes, and implement these abstractions on the third | fourth layer?

application architecture build code ddd deep learning deep learning projects domain domains frameworks machine machine learning machinelearning projects pytorch solution