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# @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
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