Hi, I am using a set of 1D data for training and I noticed that GPU usage is quite low (<5%) and training takes very long time to finish.  I profiled my code (following instruction here: https://www.sagivtech.com/2017/09/19/optimizing-pytorch-training-code/ 804) and found that 73% of the computation time is spent on loading data.  I wonder if it is possible to load all data into GPU memory to speed up training, and tried to include pin_memory=True in my code, but it told me “cannot pin ‘torch.cuda.FloatTensor’ only CPU memory can be pinned”.  Does anyone have idea how I should do this?
Thank you!