BasicSR

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# general settings
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name: 101_EDVR_M_x4_SR_REDS_woTSA_600k_B4G8_valREDS4_wandb
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model_type: EDVRModel
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scale: 4
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num_gpu: auto  # official: 8 GPUs
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manual_seed: 10
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# dataset and data loader settings
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datasets:
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  train:
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    name: REDS
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    type: REDSDataset
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    dataroot_gt: datasets/REDS/train_sharp
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    dataroot_lq: datasets/REDS/train_sharp_bicubic
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    dataroot_flow: ~
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    meta_info_file: basicsr/data/meta_info/meta_info_REDS_GT.txt
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    val_partition: REDS4  # set to 'official' when use the official validation partition
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    io_backend:
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      type: disk
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    num_frame: 5
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    gt_size: 256
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    interval_list: [1]
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    random_reverse: false
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    use_hflip: true
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    use_rot: true
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    # data loader
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    num_worker_per_gpu: 3
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    batch_size_per_gpu: 4
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    dataset_enlarge_ratio: 200
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    prefetch_mode: ~
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  val:
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    name: REDS4
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    type: VideoTestDataset
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    dataroot_gt: datasets/REDS/train_sharp
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    dataroot_lq: datasets/REDS/train_sharp_bicubic
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    meta_info_file: basicsr/data/meta_info/meta_info_REDS4_test_GT.txt
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    # change to 'meta_info_REDSofficial4_test_GT' when use the official validation partition
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    io_backend:
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      type: disk
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    cache_data: false
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    num_frame: 5
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    padding: reflection_circle
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# network structures
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network_g:
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  type: EDVR
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  num_in_ch: 3
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  num_out_ch: 3
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  num_feat: 64
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  num_frame: 5
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  deformable_groups: 8
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  num_extract_block: 5
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  num_reconstruct_block: 10
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  center_frame_idx: ~
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  hr_in: false
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  with_predeblur: false
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  with_tsa: false
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# path
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path:
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  pretrain_network_g: ~
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  strict_load_g: true
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  resume_state: ~
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# training settings
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train:
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  ema_decay: 0.999
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  optim_g:
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    type: Adam
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    lr: !!float 4e-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: CosineAnnealingRestartLR
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    periods: [150000, 150000, 150000, 150000]
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    restart_weights: [1, 1, 1, 1]
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    eta_min: !!float 1e-7
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  total_iter: 600000
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  warmup_iter: -1  # no warm up
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  dcn_lr_mul: 1
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  # losses
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  pixel_opt:
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    type: CharbonnierLoss
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    loss_weight: 1.0
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    reduction: sum
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# validation settings
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val:
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  val_freq: !!float 5e3
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  save_img: false
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  metrics:
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    psnr: # metric name, can be arbitrary
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      type: calculate_psnr
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      crop_border: 0
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      test_y_channel: false
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# logging settings
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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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  use_tb_logger: true
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  wandb:
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    project: ~
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    resume_id: ~
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# dist training settings
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dist_params:
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  backend: nccl
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  port: 29500
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