Object detection: Enable loading from checkpoint

It would be nice if I can pass a checkpoint folder to the object detection trainer option, which can be used to save and load intermediate weight for every N epoch/step/epic. In that case I don't have to retrain the model from the beginning everytime.

In the meantime, It would also be nice if object detection trainer will return instead of throw a cancellationException when `mlcontext.CancelExcute` get called.

Both features will allow user to pause training process whenever they want and restart training from preivous progress. This would be super useful for deep learning scenarios.

**Describe the solution you'd like**
- in training option, accept a checkpoint folder
- when cancelling, don't throw error, just return current result