CPT Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accepted at ICLR 2021 (Spotlight) [Paper Link]. Overview Low-precision deep neural network (DNN) training has gained tremendous attention as reducing precision is one of the most effective knobs for boosting DNNs’ training time/energy efficiency. In this paper, we attempt to explore low-precision training from a new perspective as inspired by recent findings in understanding DNN training: we conjecture that DNNs’ precision might have a similar […]

lightweight-gan 512×512 flowers after 12 hours of training, 1 gpu 256×256 flowers after 12 hours of training, 1 gpu Pizza ‘Lightweight’ GAN Implementation of ‘lightweight’ GAN proposed in ICLR 2021, in Pytorch. The main contributions of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary “converge on single gpu with few hours’ training, on 1024 resolution sub-hundred images”. Install $ pip install lightweight-gan Use One command $ lightweight_gan […]