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# @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: 0.01
limit_val_batches: 0.1
datamodule:
batch_size: 8
# resize: [288, 320]
summary: null
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