If it interests you this seems to worklast_task = Task.get_task(project_name="playground-sandbox", task_name='foo2') task = Task.init(project_name="playground-sandbox", task_name='foo2', continue_last_task=last_task.id if last_task else None)
StaleButterfly40 , alternatively you could use auto_connect_frameworks=False
https://clear.ml/docs/latest/docs/references/sdk/task#taskinit
So torch.save won't automatically save the model, however, you will not get the scalars/metrics automatically as well.
CostlyOstrich36 Thanks!
But it seems like this only works if I am running both times from the same machine because clearml is not checking if task exists in server - it is checking if it is in cache_dir
StaleButterfly40 , it looks like there might be a good solution for your request. In the previous link I provided, there is a parameter ' continue_last_task' that should work for you 🙂
I want everything to appear in the same experiment (e.g scalar metrics)
StaleButterfly40 Hi!
You could clone the original task and edit the input model of the new task as the output model of the previous task 🙂