readme: ---
  library_name: keras
  ---
  
  VQ-GAN model trained on the Kimetsu no Yaiba dataset on Tensorflow.
  
  The parameters used for training are the following:
  
  ```yaml
  model:
    vqvae_config:
      beta: 0.25
      num_embeddings: 50257
      embedding_dim: 128
    autoencoder_config:
      z_channels: 512
      channels: 32
      channels_multiplier: 
      - 2
      - 4
      - 8
      - 8
      num_res_blocks: 1
      attention_resolution: 
      - 16
      resolution: 128
      dropout: 0.0
    discriminator_config:
      num_layers: 3
      filters: 64
      
    loss_config:
      discriminator:
        loss: "hinge"
        factor: 1.0
        iter_start: 50000000
        weight: 0.8
      vqvae:
        codebook_weight: 1.0
        perceptual_weight: 4.0
      perceptual_loss: "vgg19" # "vgg16", "vgg19", "style"
  
  trainer:
    batch_size: 64
    n_epochs: 10000
    gen_lr: 3e-5
    disc_lr: 5e-5
    gen_beta_1: 0.5
    gen_beta_2: 0.9
    disc_beta_1: 0.5
    disc_beta_2: 0.9
    gen_clip_norm: 1.0
    disc_clip_norm: 1.0
  ```
  
  Implementation and documentation can be found [here](https://github.com/Kurokabe/GANime)