Hi @ptrblck,
Yes, I’m using the torch.backends.cudnn.benchmark = True and also replaced all the try/except with conditionals and that made no difference in the performance.
Another piece of information that might be useful to determine the sink in performance is that the model I’m using is a transfer learning model which was used trained on pytorch 0.4.1. Maybe there could be a performance issue with using weights trained with a previous pytorch version?
I still haven’t been able to publicly release the code, but I can grant you read access.Do you think that might help resolve this issue?