it's a fine tuning experiment which was more convenient to do in one script
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.)
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
BTW: what's the use case? Why do you need to open two Tasks in the same code/script ?
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