# HyperGAN ## HyperGAN - [About](https://hypergan.gitbook.io/hypergan/master.md) - [Getting started](https://hypergan.gitbook.io/hypergan/gettingstarted.md) - [CLI guide](https://hypergan.gitbook.io/hypergan/cli.md) - [Configurations](https://hypergan.gitbook.io/hypergan/configuration.md) - [Configurable Parameters](https://hypergan.gitbook.io/hypergan/configuration/configurable-parameters.md) - [AI Explorer for Android](https://hypergan.gitbook.io/hypergan/projects-using-hypergan/ai-explorer-for-android.md): HyperGAN AI available on the Google Play Store - [Youtube, Twitter, Discord +](https://hypergan.gitbook.io/hypergan/projects-using-hypergan/youtube-twitter-discord-+.md): Community links - [2D](https://hypergan.gitbook.io/hypergan/examples-1/2d.md): Trains a generator to output 2d points (pixels) matching a known distribution. - [Text](https://hypergan.gitbook.io/hypergan/examples-1/text.md) - [Classification](https://hypergan.gitbook.io/hypergan/examples-1/classification.md) - [Colorizer](https://hypergan.gitbook.io/hypergan/examples-1/colorizer.md): Colorizer feeds a black and white version of the input into the generator. - [Next Frame (video)](https://hypergan.gitbook.io/hypergan/examples-1/next-frame-video.md) - [Training a GAN](https://hypergan.gitbook.io/hypergan/tutorials/training.md) - [Pygame inference](https://hypergan.gitbook.io/hypergan/tutorials/pygame.md) - [Creating an image dataset](https://hypergan.gitbook.io/hypergan/tutorials/creating-an-image-dataset.md) - [Searching for hyperparameters](https://hypergan.gitbook.io/hypergan/tutorials/searching-for-hyperparameters.md) - [GAN](https://hypergan.gitbook.io/hypergan/components/gan.md): Create the domain object map and connect all components. - [Aligned GAN](https://hypergan.gitbook.io/hypergan/components/gan/aligned-gan.md) - [Aligned Interpolated GAN](https://hypergan.gitbook.io/hypergan/components/gan/aligned-interpolated-gan.md) - [Standard GAN](https://hypergan.gitbook.io/hypergan/components/gan/standard-gan.md) - [Generator](https://hypergan.gitbook.io/hypergan/components/generator.md): Manages the network used to create fake samples. - [Configurable Generator](https://hypergan.gitbook.io/hypergan/components/generator/configurable-generator.md) - [DCGAN Generator](https://hypergan.gitbook.io/hypergan/components/generator/dcgan-generator.md) - [Resizable Generator](https://hypergan.gitbook.io/hypergan/components/generator/resizable-generator.md) - [Discriminator](https://hypergan.gitbook.io/hypergan/components/discriminator.md): Manages the network used to discriminate real/fake samples. - [DCGAN Discriminator](https://hypergan.gitbook.io/hypergan/components/discriminator/dcgan-discriminator.md) - [Configurable Discriminator](https://hypergan.gitbook.io/hypergan/components/discriminator/configurable-discriminator.md) - [Layers](https://hypergan.gitbook.io/hypergan/components/layers.md) - [add](https://hypergan.gitbook.io/hypergan/components/layers/add.md) - [cat](https://hypergan.gitbook.io/hypergan/components/layers/cat.md) - [channel\_attention](https://hypergan.gitbook.io/hypergan/components/layers/channel_attention.md) - [ez\_norm](https://hypergan.gitbook.io/hypergan/components/layers/ez_norm.md) - [layer](https://hypergan.gitbook.io/hypergan/components/layers/layer.md) - [mul](https://hypergan.gitbook.io/hypergan/components/layers/mul.md) - [multi\_head\_attention](https://hypergan.gitbook.io/hypergan/components/layers/multi_head_attention.md) - [operation](https://hypergan.gitbook.io/hypergan/components/layers/operation.md) - [pixel\_shuffle](https://hypergan.gitbook.io/hypergan/components/layers/pixel_shuffle.md) - [residual](https://hypergan.gitbook.io/hypergan/components/layers/residual.md) - [resizable\_stack](https://hypergan.gitbook.io/hypergan/components/layers/resizable_stack.md) - [segment\_softmax](https://hypergan.gitbook.io/hypergan/components/layers/segment_softmax.md) - [upsample](https://hypergan.gitbook.io/hypergan/components/layers/upsample.md) - [Loss](https://hypergan.gitbook.io/hypergan/components/loss.md): Losses define how the error signals are interpreted for the two GAN players. - [ALI Loss](https://hypergan.gitbook.io/hypergan/components/loss/ali-loss.md): layer add for configurable component - [F Divergence Loss](https://hypergan.gitbook.io/hypergan/components/loss/f-divergence-loss.md) - [Least Squares Loss](https://hypergan.gitbook.io/hypergan/components/loss/least-squares-loss.md) - [Logistic Loss](https://hypergan.gitbook.io/hypergan/components/loss/logistic-loss.md) - [QP Loss](https://hypergan.gitbook.io/hypergan/components/loss/qp-loss.md): https://arxiv.org/abs/1811.07296 - [RAGAN Loss](https://hypergan.gitbook.io/hypergan/components/loss/ragan-loss.md) - [Realness Loss](https://hypergan.gitbook.io/hypergan/components/loss/realness-loss.md) - [Softmax Loss](https://hypergan.gitbook.io/hypergan/components/loss/softmax-loss.md) - [Standard Loss](https://hypergan.gitbook.io/hypergan/components/loss/standard-loss.md) - [Wasserstein Loss](https://hypergan.gitbook.io/hypergan/components/loss/wasserstein-loss.md) - [Latent](https://hypergan.gitbook.io/hypergan/components/latent.md): Describes a prior distribution that feeds to a generator - [Uniform Distribution](https://hypergan.gitbook.io/hypergan/components/latent/uniform-distribution.md) - [Trainer](https://hypergan.gitbook.io/hypergan/components/trainer.md): Trains the GAN object. - [Alternating Trainer](https://hypergan.gitbook.io/hypergan/components/trainer/alternating-trainer.md) - [Simultaneous Trainer](https://hypergan.gitbook.io/hypergan/components/trainer/simultaneous-trainer.md) - [Balanced Trainer](https://hypergan.gitbook.io/hypergan/components/trainer/balanced-trainer.md) - [Accumulate Gradient Trainer](https://hypergan.gitbook.io/hypergan/components/trainer/accumulate-gradient-trainer.md) - [Optimizer](https://hypergan.gitbook.io/hypergan/components/optimizer.md): Optimizers move weights along gradients. They are managed by the trainer. - [Train Hook](https://hypergan.gitbook.io/hypergan/components/trainhook.md): Train hooks provide training events and loss modification to trainers. - [Adversarial Norm](https://hypergan.gitbook.io/hypergan/components/trainhook/adversarial-norm.md): Custom research - [Weight Constraint](https://hypergan.gitbook.io/hypergan/components/trainhook/weight-constraint.md) - [Stabilizing Training](https://hypergan.gitbook.io/hypergan/components/trainhook/stabilizing-training.md): https://github.com/rothk/Stabilizing\_GANs - [JARE](https://hypergan.gitbook.io/hypergan/components/trainhook/jare.md): https://arxiv.org/abs/1806.09235 - [Learning Rate Dropout](https://hypergan.gitbook.io/hypergan/components/trainhook/learning-rate-dropout.md): https://arxiv.org/abs/1912.00144 - [Gradient Penalty](https://hypergan.gitbook.io/hypergan/components/trainhook/gradient-penalty.md): https://arxiv.org/pdf/1704.00028.pdf - [Rolling Memory](https://hypergan.gitbook.io/hypergan/components/trainhook/rolling-memory.md): (no paper) - [Other GAN implementations](https://hypergan.gitbook.io/hypergan/components/other-gan-implementations.md): Linked with awe --- # Agent Instructions This documentation is published with GitBook. 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