What are the modules of the Generative Adversarial Network in Torch?

In Torch, there are several commonly used libraries for generating adversarial networks (GAN) modules.

1. successive
2. The nn.Linear function
3. a two-dimensional convolutional neural network layer
4. This refers to a 2-dimensional batch normalization operation.
5. Rectified Linear Unit
6. Leaky rectified linear unit (ReLU)
7. the nn.Sigmoid function
8. Binary Cross Entropy Loss
9. Mean Absolute Error
10. Mean squared error loss

These modules can be combined together to build a generative adversarial network, where the generator and discriminator are trained to produce samples that closely resemble real data in order to deceive the discriminator.