HappyLion37 did you check the https://github.com/allegroai/trains/tree/master/examples/services/hyper-parameter-optimization ?
You can very quickly get it distributed as well
it's a fine tuning experiment which was more convenient to do in one script
BTW: what's the use case? Why do you need to open two Tasks in the same code/script ?
it worked! thanks Martin. But I still don't understand why using Task.create failed. It wouldn't create a new experiment even if I did not close anything
Hi HappyLion37
It seems that you are "reusing" the Tasks. Which means the second time you open them you are essentially resetting the old run and starting all over.
Try to do:task1 = Task.init('examples', 'step one', reuse_last_task_id=False) print('do stuff') task1.close() task2 = Task.init('examples', 'step two', reuse_last_task_id=False) print('do some more stuff') task2.close()
Task.create
will create a new Task (and return an object) but it does not do any auto-magic (like logging the console, tensorboard etc.)