How to Realize 'Gradient Reversal Layer' ?
6 visualizzazioni (ultimi 30 giorni)
Mostra commenti meno recenti
How can i complete a 'Gradient Reversal Layer' in matlab like in pytorch or tensorflow?
It is normally used in transfer learning network when a GAN-like loss is adopted.
Could i realize it by define a custom layer?
It is very grateful if you can offer an example of some detailed advice. Thank you for your help.
2 Commenti
Risposta accettata
Philip Brown
il 21 Giu 2021
It looks like you should be able to do this by writing your own custom layer. See the "Intermediate Layer Template" for some code to get started.
There's a custom layer used in a visualization example which does something a little bit similar (to modify the behavior of a ReLU gradient), here.
I think the custom layer code you need looks something like this:
classdef GradientReversalLayer < nnet.layer.Layer
methods
function Z = predict(layer, X)
Z = X; % Identity
end
function dLdX = backward(layer, X, dLdZ)
dLdX = -dLdZ; % Reverse gradient
end
end
end
If you want to define the constant you multiple the gradient by, you could make it a property of the custom layer and include that in your backward function.
Più risposte (0)
Vedere anche
Categorie
Scopri di più su Image Data Workflows in Help Center e File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!