How does the choice of activation function in the generator impact the stability of GAN training?Question 21Answera.It can speed up the convergence speed but not stabilityb.It has no impact on stabilityc.It can even lead to vanishing gradients and instability due to slow convergenced.It ensures smooth gradients and stable training

Which architecture can help address convergence issues in traditional GANs?RNNDBNWGANCNNLSTM

Which technique can help in dealing with training instability in GANs?Noise additionAll of the given optionsGradient clippingData augmentationDropout

Which of the following best describes the role of the generator in a GAN?To critique imagesTo produce imagesNone of the given optionsTo combine imagesTo evaluate the loss

Key Changes:Reduced Model Complexity: The discriminator model now has fewer layers, which speeds up training.Increased Batch Size: Using a batch size of 64 instead of 32 will make each epoch faster.Reduced Epochs: Set epochs to 10,000 instead of 20,000 to save time while still producing good results.These changes should help reduce the time it takes to train your GAN and generate samples, while still providing high-quality synthetic data.

Which challenge refers to the generator producing limited varieties or even the same sample every time?Training InstabilityAll of the given optionsConvergence IssuesData AugmentationMode Collapse