Question 13: In a GAN training loop, the following function is used b…

In a GAN training loop, the following function is used before each backward pass:

Suppose a GAN is trained and this function is used in every iteration with learning rate α = 0.01 :
During iteration 1:
The true discriminator gradient (∇θ_D L_D) = 0.6 The true generator gradient (∇θ_G L_G) = 0.5
During iteration 2:
The new discriminator gradient (∇θ_D L_D) = 0.4 The new generator gradient (∇θ_G L_G) = 0.2
What will be the effective parameter update after the second iteration (assume gradients accumulate linearly in PyTorch)?