# @package _global_

defaults:
  - override /network: vqvae
  - override /criterion: mse
  - override /model: lit_vqvae
  - override /callbacks: wandb_vae
  - override /optimizers: null
  # - override /lr_schedulers: 
      # - cosine_annealing

# lr_schedulers: null
#   network:
#     _target_: torch.optim.lr_scheduler.OneCycleLR
#     max_lr: 1.0e-2
#     total_steps: null
#     epochs: 100
#     steps_per_epoch: 200
#     pct_start: 0.1
#     anneal_strategy: cos
#     cycle_momentum: true
#     base_momentum: 0.85
#     max_momentum: 0.95
#     div_factor: 25
#     final_div_factor: 1.0e4
#     three_phase: true
#     last_epoch: -1
#     verbose: false

#     # Non-class arguments
#     interval: step
#     monitor: val/loss

optimizers:
  network:
    _target_: madgrad.MADGRAD
    lr: 1.0e-4
    momentum: 0.9
    weight_decay: 0
    eps: 1.0e-7

    parameters: network

trainer:
  max_epochs: 128
  limit_train_batches: 0.1
  limit_val_batches: 0.1

datamodule:
  batch_size: 8
  # resize: [288, 320]

summary: null