Can someone please make it clear for me what is the difference the loss.backward() and loss.mean().backward()? confusion overloads 
The  loss is loss = criterion(output, label)
where/when should i do   loss.backward and in what senario should i do loss.mean().backward()?
does it have anything to do with batchsize and number of GPUs that are being used?
can it cause a problem or is it wrong if I use one instead of another carelessly?
Thanks