[TensorFlow] Generative Adversarial Nets (GAN)

TensorFlow implementation of Generative Adversarial Networks (GAN) with MNIST dataset.

Architecture

Training algorithm

The algorithm for training GAN [1].

GAN architecture

The architecture of GAN [1].

Graph in TensorBoard

Graph of GAN.

Results

Training Procedure

Loss graph in the training procedure.
Each graph shows loss of the discriminator and loss of the generator respectively.

Test Procedure

z:2	z:2 (latent space walking)

z:64	z:128

Environment

• Python 3.7.4
• Tensorflow 1.14.0
• Numpy 1.17.1
• Matplotlib 3.1.1
• Scikit Learn (sklearn) 0.21.3

Reference

[1] Ian Goodfellow et al. (2014). Generative Adversarial Nets. NIPS (NeurIPS).