81 lines
1.6 KiB
YAML
81 lines
1.6 KiB
YAML
#### general settings
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name: 002_EDVR_EDVRwoTSAIni_lr4e-4_600k_REDS_LrCAR4S_fixTSA50k_new
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use_tb_logger: true
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model: video_base
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distortion: sr
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scale: 4
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gpu_ids: [0,1,2,3,4,5,6,7]
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#### datasets
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datasets:
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train:
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name: REDS
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mode: REDS
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interval_list: [1]
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random_reverse: false
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border_mode: false
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dataroot_GT: ../datasets/REDS/train_sharp_wval.lmdb
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dataroot_LQ: ../datasets/REDS/train_sharp_bicubic_wval.lmdb
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cache_keys: ~
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N_frames: 5
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use_shuffle: true
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n_workers: 3 # per GPU
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batch_size: 32
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target_size: 256
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LQ_size: 64
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use_flip: true
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use_rot: true
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color: RGB
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val:
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name: REDS4
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mode: video_test
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dataroot_GT: ../datasets/REDS4/GT
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dataroot_LQ: ../datasets/REDS4/sharp_bicubic
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cache_data: True
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N_frames: 5
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padding: new_info
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#### network structures
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network_G:
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which_model_G: EDVR
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nf: 64
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nframes: 5
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groups: 8
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front_RBs: 5
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back_RBs: 10
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predeblur: false
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HR_in: false
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w_TSA: true
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#### path
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path:
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pretrain_model_G: ../experiments/pretrained_models/EDVR_REDS_SR_M_woTSA.pth
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strict_load: false
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resume_state: ~
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#### training settings: learning rate scheme, loss
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train:
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lr_G: !!float 4e-4
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lr_scheme: CosineAnnealingLR_Restart
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beta1: 0.9
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beta2: 0.99
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niter: 600000
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ft_tsa_only: 50000
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warmup_iter: -1 # -1: no warm up
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T_period: [50000, 100000, 150000, 150000, 150000]
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restarts: [50000, 150000, 300000, 450000]
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restart_weights: [1, 1, 1, 1]
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eta_min: !!float 1e-7
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pixel_criterion: cb
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pixel_weight: 1.0
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val_freq: !!float 5e3
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manual_seed: 0
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#### logger
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logger:
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print_freq: 100
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save_checkpoint_freq: !!float 5e3
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