GAN-PyTorch

Incremental implementation of Generative Adversarial Networks using PyTorch for MNIST dataset.

There are four implemetations:

1. A GAN with linear layers only.
2. A GAN with linear layers and batch normalization
3. A GAN with 2D CNN layers and 2D Batch Normalization
4. A GAN with 2D CNN layers and Spectral Normalization

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Results

All models have been trained for the same number of epochs (50) to compare the differences between the four techniques.

Vanilla GAN	GAN and BN	DCGAN	DCGAN+Spetral Norm.