The pytorch version is: 1.0.0a0+14004cb which is the current version on Master branch. The python version is: 2.7.15. And I am using 2 GPUs. Any idea is appreciated. Thanks in advance!
This is not really easily readable code… A smaller example that reproduces just this issue would be more helpful
I would check that torch.cat((s_input_var, t_input_var), dim=0) this op actually returns enough sample for the data parallel to work wiht? Or is it explicitly done such that s_* run on one gpu and t_* runs on the other and you always have 2 gpus?
I’m new to PyTorch. After I printed out s_input_var and t_input_var it seems that they are both on the same GPU with device='cuda:0'. Do they need to be on different GPUs? They are calculated in the following way:
Hi,
I have a similar issue. The question you are asking about parts use different GPUs is the case in mine. (I don’t use data parallelism).
If I use different GPUs and concat, does the loss function need to be changed? (I get the same exception.)