Comments (6)
1 GPU using batchsize 2 yes?
from few-shot-vid2vid.
Try with 1 GPU- I think you've got an error that you can't see that you're hung up on.
The model hyper parameters seem to tweak themselves as training proceeds- it reports things like adjustments to the learning rate and 'training sequence length.' I wonder if one of these automatic adjustments causes an issue- I'd have said you were running out of memory but you said you dropped the batch size already.
from few-shot-vid2vid.
Did you have a performance difference between 1x VideoCard vs 2x VideoCards?
I have no difference at all, the same performance.
2x GTX1080ti
from few-shot-vid2vid.
I haven't trained using just one GPU, I used both through out, it's only when I run the test scripts that I run on the second GPU specifically, adding the finetune argument causes the first GPU to dump the core...
Are you using the latest source?
from few-shot-vid2vid.
Yes. The same story with the recent and previous versions. The only difference while using multiple gpu, I can double --batchSize (8 against 4). But it doesn't affect performance
from few-shot-vid2vid.
This repo is now deprecated. Please refer to the new Imaginaire repo: https://github.com/NVlabs/imaginaire.
from few-shot-vid2vid.
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