stability config: 4x_SPAN_S_clean_fidelity.yml
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docs/stability/clean/configs/4x_SPAN_S_clean_fidelity.yml
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name: 4x_SPAN_S_clean_fidelity
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scale: 4
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use_amp: true
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amp_bf16: true
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use_channels_last: true
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fast_matmul: false
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use_compile: false
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compile_mode: default
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num_gpu: auto
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manual_seed: 1024
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datasets:
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train:
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name: LUCID Train
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type: pairedimagedataset
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dataroot_gt: [datasets/train/lucid_hc512/hr]
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dataroot_lq: [datasets/train/lucid_hc512/lr_x4]
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lq_size: 96
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use_hflip: true
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use_rot: true
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num_worker_per_gpu: 8
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batch_size_per_gpu: 8
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accum_iter: 1
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val:
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name: Urban100 Val
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type: pairedimagedataset
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dataroot_gt: [datasets/val/urban100/hr]
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dataroot_lq: [datasets/val/urban100/lr_x4]
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filename_tmpl: "{}x4" # Urban100 LR files are named img_001x4.png
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network_g:
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type: span_s
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norm: false
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path:
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param_key_g: ~
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strict_load_g: true
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resume_state: ~
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train:
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ema_decay: 0.999
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ema_power: 0.75
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grad_clip: false
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grad_clip_max_norm: 100
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optim_g:
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type: AdamW
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lr: !!float 2e-4
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weight_decay: 0
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betas: [0.9, 0.99]
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scheduler:
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type: MultiStepLR
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milestones: [10000, 16000]
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gamma: 0.5
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total_iter: 20000
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warmup_iter: -1
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losses:
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- type: charbonnierloss
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loss_weight: 1.0
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- type: perceptualloss
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criterion: charbonnier
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loss_weight: 0.01
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- type: mssimloss
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loss_weight: 0.5
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val:
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val_enabled: true
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val_freq: 2000
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save_img: false
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tile_size: 0
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tile_overlap: 8
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metrics_enabled: true
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metrics:
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psnr:
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type: calculate_psnr
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crop_border: 4
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test_y_channel: true
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ssim:
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type: calculate_ssim
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crop_border: 4
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test_y_channel: true
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logger:
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print_freq: 100
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save_checkpoint_freq: 1000
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save_checkpoint_format: safetensors
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use_tb_logger: true
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