I have created the fast ai environment on my windows 10 laptop and everything installed properly. I was running the lesson-1.ipynb and found that my gpu utilization is low (about 8-10%) where as the CPU utilization goes even up to 75%. I don’t understand why is this happening.
torch.cuda.is_available() shows True when executed and torch.backends.cudnn.enabled also shows True
I looked into my task manager under the Performance section and found that dedicated gpu memory for pytorch is showing 1gb / 4 gb (I have a gtx 1050ti laptop), but I also have a tensorflow-gpu environment and when I run any model on that written in tensorflow / Keras ,the gpu utilization is 30-40% and dedicated memory is 3gb / 4gb. Is pytorch working normally or is somehing wrong?
Thanks in advance.