GFPGAN

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num_gpu: 1
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manual_seed: 0
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is_train: True
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dist: False
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# network structures
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network_g:
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  type: GFPGANv1
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  out_size: 512
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  num_style_feat: 512
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  channel_multiplier: 1
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  resample_kernel: [1, 3, 3, 1]
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  decoder_load_path: ~
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  fix_decoder: true
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  num_mlp: 8
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  lr_mlp: 0.01
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  input_is_latent: true
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  different_w: true
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  narrow: 0.5
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  sft_half: true
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network_d:
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  type: StyleGAN2Discriminator
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  out_size: 512
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  channel_multiplier: 1
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  resample_kernel: [1, 3, 3, 1]
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network_d_left_eye:
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  type: FacialComponentDiscriminator
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network_d_right_eye:
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  type: FacialComponentDiscriminator
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network_d_mouth:
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  type: FacialComponentDiscriminator
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network_identity:
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  type: ResNetArcFace
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  block: IRBlock
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  layers: [2, 2, 2, 2]
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  use_se: False
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# path
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path:
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  pretrain_network_g: ~
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  param_key_g: params_ema
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  strict_load_g: ~
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  pretrain_network_d: ~
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  pretrain_network_d_left_eye: ~
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  pretrain_network_d_right_eye: ~
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  pretrain_network_d_mouth: ~
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  pretrain_network_identity: ~
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  # resume
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  resume_state: ~
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  ignore_resume_networks: ['network_identity']
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# training settings
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train:
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  optim_g:
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    type: Adam
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    lr: !!float 2e-3
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  optim_d:
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    type: Adam
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    lr: !!float 2e-3
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  optim_component:
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    type: Adam
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    lr: !!float 2e-3
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  scheduler:
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    type: MultiStepLR
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    milestones: [600000, 700000]
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    gamma: 0.5
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  total_iter: 800000
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  warmup_iter: -1  # no warm up
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  # losses
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  # pixel loss
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  pixel_opt:
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    type: L1Loss
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    loss_weight: !!float 1e-1
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    reduction: mean
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  # L1 loss used in pyramid loss, component style loss and identity loss
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  L1_opt:
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    type: L1Loss
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    loss_weight: 1
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    reduction: mean
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  # image pyramid loss
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  pyramid_loss_weight: 1
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  remove_pyramid_loss: 50000
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  # perceptual loss (content and style losses)
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  perceptual_opt:
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    type: PerceptualLoss
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    layer_weights:
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      # before relu
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      'conv1_2': 0.1
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      'conv2_2': 0.1
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      'conv3_4': 1
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      'conv4_4': 1
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      'conv5_4': 1
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    vgg_type: vgg19
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    use_input_norm: true
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    perceptual_weight: !!float 1
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    style_weight: 50
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    range_norm: true
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    criterion: l1
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  # gan loss
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  gan_opt:
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    type: GANLoss
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    gan_type: wgan_softplus
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    loss_weight: !!float 1e-1
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  # r1 regularization for discriminator
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  r1_reg_weight: 10
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  # facial component loss
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  gan_component_opt:
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    type: GANLoss
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    gan_type: vanilla
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    real_label_val: 1.0
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    fake_label_val: 0.0
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    loss_weight: !!float 1
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  comp_style_weight: 200
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  # identity loss
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  identity_weight: 10
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  net_d_iters: 1
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  net_d_init_iters: 0
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  net_d_reg_every: 1
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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: True
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  use_pbar: True
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  metrics:
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    psnr: # metric name
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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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