Recall & Review
beginner
What is the role of the generator in a GAN?
The generator creates fake data that looks like real data to fool the discriminator.
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beginner
What does the discriminator do in a GAN?
The discriminator tries to tell apart real data from fake data produced by the generator.
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intermediate
Why do the generator and discriminator compete in GAN training?
They compete so the generator improves at making realistic data, and the discriminator improves at spotting fakes.
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intermediate
In PyTorch, what is a simple way to define a generator model?
Use torch.nn.Module to build layers that take random noise as input and output fake data.
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intermediate
What loss function is commonly used for the discriminator in GANs?
Binary cross-entropy loss is used to measure how well the discriminator classifies real vs fake data.
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What input does the generator in a GAN usually take?
✗ Incorrect
The generator starts from random noise to create new fake data.
What is the main goal of the discriminator?
✗ Incorrect
The discriminator learns to tell real data from fake data.
Which loss function is typically used to train the discriminator?
✗ Incorrect
Binary cross-entropy measures how well the discriminator classifies real vs fake.
During GAN training, what happens when the discriminator gets better?
✗ Incorrect
A stronger discriminator pushes the generator to create more realistic data.
Which PyTorch class is used to create generator and discriminator models?
✗ Incorrect
torch.nn.Module is the base class for all neural network models in PyTorch.
Explain how the generator and discriminator work together in a GAN.
Think of a game where one tries to fool and the other tries to detect.
You got /4 concepts.
Describe how you would implement a simple generator model in PyTorch.
Start from random noise and build a small neural network.
You got /4 concepts.