Develop a GAN with Pytorch

Implement and train GAN in Python and Pytorch.

Let’s see all of that in action and build a GAN from scratch.

After importing our standard Pytorch modules, we will define the generator and the discriminator. Both of them are simple multi-layer networks.

Generator

  • Receives as input 100-length noise vector zz sampled from a distribution
  • Outputs a flattened image in the dimensions of the cifar10 dataset:
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