# @package _global_

defaults:
  - override /network: vqvae
  - override /criterion: vqgan_loss
  - override /model: lit_vqgan
  - override /callbacks: wandb_vae
  - override /optimizers: null
  - override /lr_schedulers: null

datamodule:
  batch_size: 8

lr_schedulers:
  generator:
    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
    T_max: 256
    eta_min: 0.0
    last_epoch: -1

    interval: epoch
    monitor: val/loss

  discriminator:
    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
    T_max: 256
    eta_min: 0.0
    last_epoch: -1

    interval: epoch
    monitor: val/loss

optimizers:
  generator:
    _target_: madgrad.MADGRAD
    lr: 2.0e-5
    momentum: 0.5
    weight_decay: 0
    eps: 1.0e-6

    parameters: network

  discriminator:
    _target_: madgrad.MADGRAD
    lr: 2.0e-5
    momentum: 0.5
    weight_decay: 0
    eps: 1.0e-6

    parameters: loss_fn.discriminator

trainer:
  max_epochs: 256
  # gradient_clip_val: 0.25

summary: null