My third GAN after the previous one. Trained on with PyTorch and manually exported to WebGL 2.0.
This version uses a variational autoencoder, which produces results with higher variety and more accurate colors.
==== Generator ==== Latent - 32 Dense layer - 512x32 => 512, LeakyReLU(0.1) Reshape to 32x4x4 ConvTranspose2d - 32x64x4x4 => 64x8x8, BatchNorm2d, LeakyReLU(0.1) ConvTranspose2d - 64x32x4x4 => 32x16x16, BatchNorm2d, LeakyReLU(0.1) ConvTranspose2d - 32x16x4x4 => 16x32x32, BatchNorm2d, LeakyReLU(0.1) ConvTranspose2d - 16x3x4x4 => 3x64x64, Sigmoid