Hi,
This might be a fundamentally absurd question, however, I just wanted to understand what am I not understanding right.
So, to use the GPU to train the model, I did the following obvious things:
inputs,labels = data[0].to(torch_device),data[1].to(torch_device)
and this worked well.
However, before this, I had tried the following:
inputs,labels = data
inputs.to(torch_device)
labels.to(torch_device)

but this did not work as when I checked
input.is_cuda
it returned false.
Now, one more look into it and I understood the difference - input was already a tensor and I was trying to transfer that to the gpu, which fails, whereas when I transfer data, a list, first to the gpu and then create the tensor there, that works perfectly.
Is there a specific reason why a tensor created on the cpu can’t be transferred as is to the GPU?
Thanks