I’m not sure if this was solved, but I am encountering a similar issue. From what I see it all depends on what multiprocessing start method is used.
When using fork ClearML works fine and it’s able to capture everything, however it is not recommended to use fork as it is not safe with multithreading (e.g. see None ).
With spawn and forkserver (which is used in the script above) ClearML is not able to automatically capture PyTorch scalars and artifacts. For what concerns spawn I think the reason is that a whole new python process is started from scratch. For forkserver I am not sure on the reason, as it should inherit some of the parent process memory.

Did anyone else encounter this issue in the meantime? Any solutions?