is there any document for this?

Sure I'm right here with you

Here is the screenshot

Yes, i think trains might wrap the torch.load function, but the thing is that i need to load some part of the dataset using torch.load, so this error shows up many time during training, I found i can use this line:
task = Task.init(project_name="Alfred", task_name="trains_plot", auto_connect_frameworks={'pytorch': False})but does it mean i cannot monitor torch.load function any more?

one quick question is that do i need to do some task.close() at the end of each process?

seems the not logging problem is back

Nice job

I have two laptop, one is running ubuntu 20.04 and one is macos, both are running in my local network. I installed the server on ubuntu and ssh from mac to it to bring up the server then build up a tunnel using ssh -L

i can only see the init log

On sec

I can comment it on the github issue

You can use this to reproduce

Thanks man!

in my case, we need to evaluate the result across many random seeds, so each task needs to log the result independently.

I think this is not related to pytorch, because it shows the same problem with mp spawn

I'm checking it out today and see if I can put up something

Yeah the ultimate goal I'm trying to achieve is to flexibly running tasks for example before running, could have a claim saying how many resources I can and the agent will run as soon as it find there are enough resources

and one experiment takes 40 hours to run, so i let them run in parallel

yes

yes

what i want to do is to init one task and multiple works can log with this one task in parallel. TimelyPenguin76

Yeah, i’m done with the test, not i can run as what you said

Ok, i’ll try to do that asap

I’ll get back to you after i get this done