Hello, I know that this is a question probably asked quite often on this forum, but after going through the forum posts, I still am perplexed and could use some clarification. I am running Pytorch 1.6.0 on Ubuntu 20.04 with Cuda Toolkit 11.0 installed (hopefully, that’s all I needed to get everything running smoothly), and I am running some models on my local GPU.
Some models are as small as a few dense layers while I have also done transfer learning with the densenet121 model. I can tell that my GPU is being used via Nvidia X Server and by printing my Tensors to see that they have been loaded onto my GPU. However, I can also see that my CPU usage has increased significantly (to a much more significant degree on the densenet121 model of course) even when the GPU is being used. Is this normal?