Hi everyone!
I am in a bit of a pickle here.
I have the current situation: after getting the output from a simple neural network, let’s call this x, x is then used in another process, said process subsequently yields a result which is evaluated to compute a reward, which I then use to compute a loss function.
The x tensor object is not directly connected to the process, since I can only take the x.item<>() values to use it in the process. Hence, the output of the neural network is not directly connected to the loss function.
Is there a simple (or any) way in which the output tensor x could be connected to the loss function given the setting I described? This would be necessary to perform backpropagation given the loss function.
Thank you very much.