google/compare_gan

Health v2 · maintenance only

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1815 stars · 309 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A TensorFlow library from Google Research providing configurable implementations of GAN components: losses, penalties, normalization techniques, architectures (BigGAN, ResNet, DCGAN), and evaluation metrics (FID, Inception Score, precision-recall, KID). It was used to support several published GAN research papers.

Use cases

• compare GAN losses and architectures in a large-scale study
• compute FID and Inception Score for generative models
• train BigGAN or DCGAN models in TensorFlow
• evaluate precision and recall of generative models
• reproduce GAN research paper experiments
• benchmark GAN training on GPU or TPU

When to choose

• you need standardized, paper-backed GAN evaluation metrics like FID, KID, or precision-recall
• you want to reproduce or extend Google's GAN comparison studies
• you work in TensorFlow and need configurable GAN training components via Gin

When to avoid

• you want to train GANs in PyTorch or JAX
• you need actively maintained code with recent updates
• you need production image generation rather than research tooling

Facets

library · maturity maintenance

machine-learning deep-learning benchmarking gpu-computing machine-learning deep-learning python gan tensorflow generative-models fid inception-score biggan research-code tpu research image-generation gpu linux

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