- Supported operations: start, resume, pause, shutdown
- pytorch-3dunet package is used as the framework to create the models

… failed

I caught an edge case, where events are blocked, because we have exited the training, and the tasks of the queue would remain unprocessed.

Creating and closing processes and threads can be quite time consuming
resulting to test timeouts if the tests performs a lot of actions.

Applying monkeypatch to a parent process won't propagated to a child process if the start method is spawn (macos) instead of fork (linux)

- To fix test on windows, convert label data to float64

The should stop callbacks are boolean, so we need to aggregate their return value. Previously the return value wasn't taken into account, and the callbacks were returning none

The enum is used for validation check before triggering one of them. Previously I was checking if the queue was alive, but that won't be enough, for example if you want to perform resume, while you are resumed, the queue is operational, but the action shouldn't be valid.

Move NamedInt and Tensor proto to a separate file so training proto can
use as well

- The inference servicer had a procedure to list the available devices.
  This is needed or the training servicer as well. So list devices is
  decoupled to be shared.