A newer version of TF-GAN (a lightweight library for training and evaluating Generative Adversarial Networks) was announced recently. TF-GAN has been used in a number of projects and papers

Github: https://github.com/tensorflow/gan

Updated Features:

Cloud TPU support: TF-GANs can be used to train GAN’s Google Cloud TPU’s.

Self-study GAN course: Open source self study GAN courses based on internal Google study materials.

PyPi package: TF-GAN can be installed with ‘pip install tensorflow-gan’ and used with ‘import tensorflow_gan as tfgan’.

GAN metrics: TF-GAN has easier metrics to compare results from papers. TF-GAN metrics are computationally-efficient and syntactically easy.

GitHub Repository: It has its own Github repository and can be accessed easily.

Colaboratory tutorials: TF-GAN can now used be used with Google GPU’s and TPU’s.

TensorFlow 2.0: TF-GAN is now compatible with TensorFlow 2.

Image source: https://medium.com/tensorflow/introducing-tf-gan-a-lightweight-gan-library-for-tensorflow-2-0-36d767e1abae

Projects using TF-GAN

In terms of projects, here are some below:

Self-Attention GAN on Cloud TPUs [Paper]

Image Extension [Paper]

BigGAN [Paper]

GANSynth [Source]

Source: https://medium.com/tensorflow/introducing-tf-gan-a-lightweight-gan-library-for-tensorflow-2-0-36d767e1abae