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TencentARC
GitHub Repository: TencentARC/GFPGAN
Path: blob/master/tests/data/test_gfpgan_model.yml
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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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