Question about GPU memory usage about cvp-mvsnet HOT 2 CLOSED

Hi @etudemin

I think there are few reasons for this:

1. By default pytorch would use cudnn auto-tuner to find the best algorithm for the task, which I believe might consume more GPU memory(if available) for a faster inference time. You might want to turn it off and also make pytorch deterministic to get the minimum memory usage. You can check this documentation for more details.
2. You might want to clean the cuda cache before you record the memory usage by using torch.cuda.empty_cache() and torch.cuda.reset_max_memory_allocated().
3. You might want to use the pytorch provided torch.cuda.max_memory_allocated() to record the maximum memory usage.

Cheers,
Jiayu

from cvp-mvsnet.

Hi @JiayuYANG

Thank you very much for the kind replies. I will try that, thanks again!

Sincerely,
etudemin

from cvp-mvsnet.