Comments (3)
I am sorry for confusing you.
According to the implementation, the total training objective is rewritten as follows:
In the implementation, the coefficient 'alpha' is set in the following line.
Line 20 in bfd5942
In fact, the discriminator has the Gradient Reversal Layer (GRL), which inverse gradients by multiplying them with '- alpha'.
By doing this, eq. 4 is achieved by just one backpropagation.
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Thank you for the clarification. I can now correlate.
Essentially you made the Lambda
in eq 4 customizable for both the L_ent and the L_adv term by specifying the beta and alpha terms separately.
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