UNet Training is not executed on GPU

[Rony_Loschitzky]

@jmandivarapu1

The best way to check is close all the other applications running. Then run watch nvidia-smi in one terminal and in the other one run your code. Then check how the gpu memory is changing. Secondly checkout your batch size if your GPU can actually fit those number of images.

Thanks for answering!
First of all - I’ve ran “nvidia-smi” before and after I ran my code and I did notice that “volatile GPU-Util” has incresed from 3% to 96% and stayed like that throughout the training proccess. also I noticed that most of the GPU RAM was being used (around 5.8G/6G) so maybe it is running on the GPU after all? the training took about 5-6 hours on a data set of 5000 images.
my batch size is 1 and i’m not sure how I should check if my GPU can actualy fit these numbers.
How do I do it?