Hi guys, I’m not really sure why this is happening but if I measure my data object, it’s about 265mb in the GPU. If I measure the model, it’s also about 300mb. But once I start training, pytorch uses up almost all my GPU memory. I can’t really understand why. I’ve set pin_memory=False in my DataLoader already and it still displays this behavior. Is there a way to trace the memory usage properly for each object? I’m only doing a single sample every time as I can’t move to batches since all my GPU is being used up.