Hello Everyone,
I have a model which has to predict 2 things, and therefore My output is of shape [batch, 2]. My Target too, is of shape [batch, 2]. I calculate the loss as follows -
dCoordinates = torch.abs(output - coordinates)
loss = torch.sum(dCoordinates, 1)
Therefore loss is of shape [batch]. How do I propagate this loss backward?
TIA
Does
loss.backward(torch.ones_like(loss))
do what you want?
thank you for your reply @gphilip
Suppose the batch size if 4. Then the loss would be something like [0,443, 0,54, 0,21, 0,534]. Each loss would correspond to the respective inputs in the batch. I want to propagate the loss backward to the network for each input.
I do not know how to do that, and I do not know whether what you suggested would do that.
Does it perform the same thing ?