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| # general settings | |
| name: GaussianColorDenoising_HINT | |
| model_type: ImageCleanModel | |
| scale: 1 | |
| num_gpu: 8 # set num_gpu: 0 for cpu mode | |
| manual_seed: 100 | |
| # dataset and data loader settings | |
| datasets: | |
| train: | |
| name: TrainSet | |
| type: Dataset_GaussianDenoising | |
| sigma_type: random | |
| sigma_range: [0,50] | |
| in_ch: 3 ## RGB image | |
| dataroot_gt: ./Denoising/Datasets/train/WB | |
| dataroot_lq: none | |
| geometric_augs: true | |
| filename_tmpl: '{}' | |
| io_backend: | |
| type: disk | |
| # data loader | |
| use_shuffle: true | |
| num_worker_per_gpu: 8 | |
| batch_size_per_gpu: 8 | |
| # -------------Progressive training-------------------------- | |
| mini_batch_sizes: [6,4,3,1,1,1] # Batch size per gpu | |
| iters: [92000,64000,48000,36000,36000,24000] | |
| gt_size: 256 # Max patch size for progressive training | |
| gt_sizes: [128,160,192,256,320,384] # Patch sizes for progressive training. | |
| ### ------------------------------------------------------------ | |
| dataset_enlarge_ratio: 1 | |
| prefetch_mode: ~ | |
| val: | |
| name: ValSet | |
| type: Dataset_GaussianDenoising | |
| sigma_test: 25 | |
| in_ch: 3 ## RGB image | |
| dataroot_gt: ./Denoising/Datasets/test/CBSD68 | |
| dataroot_lq: none | |
| gt_size: 256 | |
| io_backend: | |
| type: disk | |
| # network structures | |
| network_g: | |
| type: HINT | |
| inp_channels: 3 | |
| out_channels: 3 | |
| dim: 48 | |
| num_blocks: [4,6,6,8] | |
| num_refinement_blocks: 4 | |
| heads: [8,8,8,8] | |
| ffn_expansion_factor: 2.66 | |
| bias: False | |
| LayerNorm_type: WithBias | |
| dual_pixel_task: False | |
| # path | |
| path: | |
| pretrain_network_g: ~ | |
| strict_load_g: true | |
| resume_state: ~ | |
| # training settings | |
| train: | |
| total_iter: 300000 | |
| warmup_iter: -1 # no warm up | |
| use_grad_clip: true | |
| # Split 300k iterations into two cycles. | |
| # 1st cycle: fixed 3e-4 LR for 92k iters. | |
| # 2nd cycle: cosine annealing (3e-4 to 1e-6) for 208k iters. | |
| scheduler: | |
| type: CosineAnnealingRestartCyclicLR | |
| periods: [92000, 208000] | |
| restart_weights: [1,1] | |
| eta_mins: [0.0003,0.000001] | |
| mixing_augs: | |
| mixup: true | |
| mixup_beta: 1.2 | |
| use_identity: true | |
| optim_g: | |
| type: AdamW | |
| lr: !!float 3e-4 | |
| weight_decay: !!float 1e-4 | |
| betas: [0.9, 0.999] | |
| # losses | |
| pixel_opt: | |
| type: L1Loss | |
| loss_weight: 1 | |
| reduction: mean | |
| fft_loss_opt: | |
| type: FFTLoss | |
| loss_weight: 0.1 | |
| reduction: mean | |
| # validation settings | |
| val: | |
| window_size: 8 | |
| val_freq: !!float 4e3 | |
| save_img: false | |
| rgb2bgr: true | |
| use_image: false | |
| max_minibatch: 8 | |
| metrics: | |
| psnr: # metric name, can be arbitrary | |
| type: calculate_psnr | |
| crop_border: 0 | |
| test_y_channel: false | |
| # logging settings | |
| logger: | |
| print_freq: 1000 | |
| save_checkpoint_freq: !!float 4e3 | |
| use_tb_logger: true | |
| wandb: | |
| project: ~ | |
| resume_id: ~ | |
| # dist training settings | |
| dist_params: | |
| backend: nccl | |
| port: 29500 | |