train_deblur_celeba_config.yaml

# lightning.pytorch==2.0.0
seed_everything: 42
trainer:
  default_root_dir: './outputs/training/deblur/celeba'
  accelerator: gpu
  strategy: ddp
  devices: 8
  num_nodes: 1
  precision: bf16-mixed
  max_epochs: 300
  max_steps: -1
  overfit_batches: 0.0
  val_check_interval: 1.0
  check_val_every_n_epoch: 1
  num_sanity_val_steps: 2
  log_every_n_steps: 50
  enable_checkpointing: true
  benchmark: true
  detect_anomaly: false
  sync_batchnorm: false
  reload_dataloaders_every_n_epochs: 0
  logger: 
    class_path: lightning.pytorch.loggers.WandbLogger
    init_args:
      project: dirac-deblur-celeba
model:
  dt: 0.05
  experiment_config_file: configs/experiments/gaussian_blur.yaml
  loss_type: 'weighted_mse_x_loss'
  lr: 0.0001 
  residual_prediction: true
  model_arch: base
  weight_decay: 0.0
  logger_type: wandb
  full_val_only_last_epoch: true
  num_log_images: 10
  model_conditioning: noise
data:
  class_path: pl_modules.image_data_module.CelebaDataModule
  init_args:
    batch_size: 4
    sample_rate_dict: {'train': 1.0, 'val': 1.0, 'test': 1.0}
    distributed_sampler: true