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Simple GAN Implementation using Tensorflow 2.0

image

This is a Generative Adversarial Network (GAN) implementation for MNIST image generation. We can create a vanilla GAN and conditional GAN in about 60 lines of Tensorflow 2.0 code.

Requirements

  • Python 3
  • Tensorflow 2.0
  • CUDA 10.0 or later
  • cuDNN 7.4.1 or later
  • If your system doesn't meet these requirements, you can use Google Colaboratory (tutorial).

Results

  • Vanilla GAN

ezgif-4-da6608d7eb85

  • Conditional GAN

ezgif com-gif-maker

References