Thanks, that you are talking about is very interesting and thanks for reference, but I did not mean DataLoaders and forking strategy during having parallel threads.
I mostly care about the initialization of the models and have the ability to specify the initialization of the model in a thread-safe way.
So my suggestion append into Public API this controlling seeds technics at the level of Models, if it is possible for cases when people do not use DataLoader's.
Very often for low-level libraries - memory and logging is user-specfied callbacks, but for PyTorch in my opinion this random seeds should be controlled with allow user to control and it’s important thing for me as user.