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.
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
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