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108 × Eureka!is there any document for this?
Sure I'm right here with you
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?
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 comment it on the github issue
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
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
I’ll get back to you after i get this done