Simply load the trained shared model in a test function, that you throw as a new thread in your main.py after stoping the training threads:
def test(args, shared_model):
    model.load_state_dict(shared_model.state_dict())
    model.eval()
    [...]

or you can even just save the trained shared model and load it with a new code