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In the GAN example of the documentation, did we update D several times before updating G?

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In the following example of GAN for the deep learning toolbox ( ), did we update Discriminator D several times before updating the generator G?
As per the GAN algorithm (say the original paper of Goodfellow 2014), we would update D k-times before updating G.
But I don't think the value of k is mentioned in the example. It looks like D and G are updated together in every loops.
The relevant codes:
% Update the discriminator network parameters.
[dlnetDiscriminator.Learnables,trailingAvgDiscriminator,trailingAvgSqDiscriminator] = ...
adamupdate(dlnetDiscriminator.Learnables, gradientsDiscriminator, ...
trailingAvgDiscriminator, trailingAvgSqDiscriminator, iteration, ...
learnRateDiscriminator, gradientDecayFactor, squaredGradientDecayFactor);
% Update the generator network parameters.
[dlnetGenerator.Learnables,trailingAvgGenerator,trailingAvgSqGenerator] = ...
adamupdate(dlnetGenerator.Learnables, gradientsGenerator, ...
trailingAvgGenerator, trailingAvgSqGenerator, iteration, ...
learnRateGenerator, gradientDecayFactor, squaredGradientDecayFactor);

Answers (1)

Sourav Bairagya
Sourav Bairagya on 10 Jan 2020
GANs can be trained in many fashions. Here, discriminator, D is updated once before updating generator, G. Hence, first, discriminator, D is updated and then the generator, G is updated in every iteration.
  1 Comment
SC on 11 Apr 2020
So, to follow the original training fashion (i.e. update (D k-times and G 1-time) n times), we need to add one more inner loop to achieve that?

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