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
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]
Asif Razzaq is the CEO of Marktechpost, LLC. As a visionary entrepreneur and engineer, Asif is committed to harnessing the potential of Artificial Intelligence for social good. His most recent endeavor is the launch of an Artificial Intelligence Media Platform, Marktechpost, which stands out for its in-depth coverage of machine learning and deep learning news that is both technically sound and easily understandable by a wide audience. The platform boasts of over a million monthly views, illustrating its popularity among audiences.