Remove working options from repo
This commit is contained in:
James Betker
parent
bd4d478572
commit
cdf641e3e2
1
.gitignore
vendored
1
.gitignore
vendored
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@ -2,6 +2,7 @@ experiments/*
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results/*
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tb_logger/*
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datasets/*
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options/*
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.vscode
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*.html
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@ -1,28 +0,0 @@
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name: adrianna
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suffix: ~ # add suffix to saved images
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model: sr
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distortion: sr
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scale: 4
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crop_border: ~ # crop border when evaluation. If None(~), crop the scale pixels
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gpu_ids: [0]
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amp_opt_level: O3
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datasets:
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test_1: # the 1st test dataset
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name: kayden
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mode: LQ
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batch_size: 13
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dataroot_LQ: ..\..\datasets\kayden\images
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start_at: 0
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#### network structures
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network_G:
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which_model_G: ResGen
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nf: 256
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nb_denoiser: 20
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nb_upsampler: 10
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upscale_applications: 1
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#### path
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path:
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pretrain_model_G: ../experiments/resgen_vgg_disc_vixen_40000.pth
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@ -1,29 +0,0 @@
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name: RRDB_ESRGAN_x4
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suffix: ~ # add suffix to saved images
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model: corruptgan
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distortion: downsample
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scale: 4
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crop_border: ~ # crop border when evaluation. If None(~), crop the scale pixels
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gpu_ids: [0]
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datasets:
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test_1: # the 1st test dataset
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name: vixen
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mode: downsample
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dataroot_GT: K:\4k6k\vixen4k\hr
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dataroot_LQ: K:\4k6k\vixen4k\lr
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batch_size: 100
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n_workers: 4 # per GPU
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target_size: 64
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#### network structures
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network_G:
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which_model_G: HighToLowResNet
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in_nc: 3
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out_nc: 3
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nf: 128
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nb: 30
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#### path
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path:
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pretrain_model_G: ../experiments/blacked_adrianna_corrupt_G.pth
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@ -1,28 +0,0 @@
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name: vix_corrupt
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suffix: ~ # add suffix to saved images
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model: sr
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distortion: sr
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scale: 4
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crop_border: ~ # crop border when evaluation. If None(~), crop the scale pixels
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gpu_ids: [0]
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amp_opt_level: O3
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datasets:
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test_1: # the 1st test dataset
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name: vix_lr
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mode: LQ
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batch_size: 64
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dataroot_LQ: K:\\4k6k\\4k_closeup\\lr_corrupted
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start_at: 35000 #ready to go.
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#### network structures
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network_G:
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which_model_G: ResGenV2
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nf: 192
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nb_denoiser: 20
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nb_upsampler: 0
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upscale_applications: 0
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#### path
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path:
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pretrain_model_G: ../experiments/pretrained_corruptors/decolorize_nonoise.pth
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@ -1,90 +0,0 @@
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#### general settings
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name: corruptGAN_4k_lqprn_closeup_flat_net
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use_tb_logger: true
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model: corruptgan
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distortion: downsample
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scale: 4
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gpu_ids: [0]
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amp_opt_level: O1
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#### datasets
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datasets:
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train:
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name: blacked
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mode: downsample
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dataroot_GT: K:\\4k6k\\4k_closeup\\hr
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dataroot_LQ: E:\\4k6k\\datasets\\ultra_lowq\\for_training
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mismatched_Data_OK: true
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use_shuffle: true
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n_workers: 8 # per GPU
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batch_size: 32
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target_size: 64
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use_flip: false
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use_rot: false
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doCrop: false
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color: RGB
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val:
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name: blacked_val
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mode: downsample
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target_size: 64
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dataroot_GT: E:\\4k6k\\datasets\\blacked\\val\\hr
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dataroot_LQ: E:\\4k6k\\datasets\\blacked\\val\\lr
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#### network structures
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network_G:
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which_model_G: FlatProcessorNet
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in_nc: 3
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out_nc: 3
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nf: 32
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ra_blocks: 6
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assembler_blocks: 4
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network_D:
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#which_model_D: discriminator_vgg_128
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#in_nc: 3
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#nf: 64
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which_model_D: discriminator_resnet
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in_nc: 3
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nf: 64
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#### path
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path:
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pretrain_model_G: ../experiments/corruptGAN_4k_lqprn_closeup_flat_net/models/29000_G.pth
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pretrain_model_D: ../experiments/corruptGAN_4k_lqprn_closeup_flat_net/models/29000_D.pth
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resume_state: ../experiments/corruptGAN_4k_lqprn_closeup_flat_net/training_state/29000.state
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strict_load: true
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#### training settings: learning rate scheme, loss
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train:
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lr_G: !!float 5e-5
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weight_decay_G: 0
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beta1_G: 0.9
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beta2_G: 0.99
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lr_D: !!float 1e-4
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weight_decay_D: 0
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beta1_D: 0.9
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beta2_D: 0.99
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lr_scheme: MultiStepLR
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niter: 400000
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warmup_iter: -1 # no warm up
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lr_steps: [12000, 24000, 36000, 48000, 64000]
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lr_gamma: 0.5
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pixel_criterion: l2
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pixel_weight: !!float 1e-2
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feature_criterion: l1
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feature_weight: 0
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gan_type: gan # gan | ragan
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gan_weight: !!float 1e-1
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D_update_ratio: 1
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D_init_iters: -1
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manual_seed: 10
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val_freq: !!float 5e2
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#### logger
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logger:
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print_freq: 50
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save_checkpoint_freq: !!float 5e2
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@ -1,83 +0,0 @@
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#### general settings
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name: resgen_movies
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use_tb_logger: true
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model: srgan
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distortion: sr
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scale: 4
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gpu_ids: [0]
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amp_opt_level: O1
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#### datasets
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datasets:
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train:
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name: movies
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mode: LQGT
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dataroot_GT: F:\\upsample_reg\\for_training\\hr
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dataroot_LQ: F:\\upsample_reg\\for_training\\lr_corrupted
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doCrop: false
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use_shuffle: true
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n_workers: 8 # per GPU
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batch_size: 8
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target_size: 256
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color: RGB
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val:
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name: movies_val
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mode: LQGT
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dataroot_GT: F:\\upsample_reg\\for_training\\val\\hr
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dataroot_LQ: F:\\upsample_reg\\for_training\\val\\lr
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#### network structures
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network_G:
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which_model_G: ResGenV2
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nf: 256
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nb_denoiser: 20
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nb_upsampler: 10
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network_D:
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which_model_D: discriminator_resnet_passthrough
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nf: 64
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#### path
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path:
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#pretrain_model_G: ~
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#pretrain_model_D: ~
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strict_load: true
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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 6e-5
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weight_decay_G: 0
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beta1_G: 0.9
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beta2_G: 0.99
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lr_D: !!float 6e-5
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weight_decay_D: 0
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beta1_D: 0.9
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beta2_D: 0.99
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lr_scheme: MultiStepLR
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niter: 400000
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warmup_iter: -1 # no warm up
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lr_steps: [20000, 60000, 80000, 100000]
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lr_gamma: 0.5
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mega_batch_factor: 1
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pixel_criterion: l1
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pixel_weight: !!float 1e-2
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feature_criterion: l1
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feature_weight: 1
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feature_weight_decay: 1
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feature_weight_decay_steps: 1
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feature_weight_minimum: 1
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gan_type: gan # gan | ragan
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gan_weight: !!float 1e-2
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D_update_ratio: 1
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D_init_iters: 0
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manual_seed: 10
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val_freq: !!float 5e2
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#### logger
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logger:
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print_freq: 50
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save_checkpoint_freq: !!float 5e2
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@ -1,97 +0,0 @@
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#### general settings
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name: train_vix_corrupt
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use_tb_logger: true
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model: corruptgan
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distortion: downsample
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scale: 1
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gpu_ids: [0]
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amp_opt_level: O0
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#### datasets
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datasets:
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train:
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name: blacked
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mode: downsample
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dataroot_GT: E:\\4k6k\\datasets\\vixen\\4k_closeup\\lr_corrupted
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dataroot_LQ: G:\\data\\pr_upsample\\ultra_lowq\\for_training\\lr
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mismatched_Data_OK: true
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use_shuffle: true
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n_workers: 12 # per GPU
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batch_size: 24
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target_size: 64
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use_flip: false
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use_rot: false
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doCrop: false
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color: RGB
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val:
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name: blacked_val
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mode: downsample
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target_size: 64
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dataroot_GT: E:\\4k6k\\datasets\\vixen\\val
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dataroot_LQ: E:\\4k6k\\datasets\\vixen\\val
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#### network structures
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network_G:
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which_model_G: ResGenV2
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nf: 192
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nb_denoiser: 20
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nb_upsampler: 0
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upscale_applications: 0
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inject_noise: False
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network_D:
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which_model_D: discriminator_vgg_128
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in_nc: 3
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nf: 64
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#### path
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path:
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pretrain_model_G: ~
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pretrain_model_D: ~
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resume_state: ../experiments/train_vix_corrupt/training_state/47000.state
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strict_load: true
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#### training settings: learning rate scheme, loss
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train:
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lr_G: !!float 1e-4
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weight_decay_G: 0
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beta1_G: 0.9
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beta2_G: 0.99
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lr_D: !!float 1e-4
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weight_decay_D: 0
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beta1_D: 0.9
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beta2_D: 0.99
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D_noise_theta_init: .01
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D_noise_final_it: 20000
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D_noise_theta_floor: .005
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lr_scheme: MultiStepLR
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niter: 400000
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warmup_iter: -1 # no warm up
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lr_steps: [15000, 50000, 100000, 200000]
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lr_gamma: 0.5
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pixel_criterion: l2
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pixel_weight: !!float 1e-2
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feature_criterion: l1
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feature_weight: .5
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feature_weight_decay: .98
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feature_weight_decay_steps: 1000
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feature_weight_minimum: .5
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gan_type: ragan # gan | ragan
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gan_weight: .1
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mega_batch_factor: 1
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swapout_G_freq: 113
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swapout_D_freq: 223
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swapout_duration: 40
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D_update_ratio: 1
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D_init_iters: -1
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manual_seed: 10
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val_freq: !!float 5e2
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#### logger
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logger:
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print_freq: 50
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save_checkpoint_freq: 500
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@ -1,97 +0,0 @@
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#### general settings
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name: train_vix_corrupt_tiled
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use_tb_logger: true
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model: corruptgan
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distortion: downsample
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scale: 1
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gpu_ids: [0]
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amp_opt_level: O0
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#### datasets
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datasets:
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train:
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name: vix_corrupt
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mode: downsample
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dataroot_GT: H:\\vix\\lr
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dataroot_LQ: H:\\ultra_lq\\tiled\\lr
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mismatched_Data_OK: true
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use_shuffle: true
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n_workers: 14 # per GPU
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batch_size: 48
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target_size: 64
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use_flip: true
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use_rot: true
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doCrop: false
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color: RGB
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val:
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name: vix_val
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mode: downsample
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target_size: 64
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dataroot_GT: E:\\4k6k\\datasets\\vixen\\val
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dataroot_LQ: E:\\4k6k\\datasets\\vixen\\val
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#### network structures
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network_G:
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which_model_G: ResGenV2
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nf: 192
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nb_denoiser: 20
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nb_upsampler: 0
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upscale_applications: 0
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inject_noise: False
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network_D:
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which_model_D: discriminator_vgg_128
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in_nc: 3
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nf: 64
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#### path
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path:
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pretrain_model_G: ~
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pretrain_model_D: ~
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resume_state: ../experiments/train_vix_corrupt_tiled/training_state/16000.state
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strict_load: true
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#### training settings: learning rate scheme, loss
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train:
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lr_G: !!float 1e-4
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weight_decay_G: 0
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beta1_G: 0.9
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beta2_G: 0.99
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lr_D: !!float 1e-4
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weight_decay_D: 0
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beta1_D: 0.9
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beta2_D: 0.99
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D_noise_theta_init: .01
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D_noise_final_it: 20000
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D_noise_theta_floor: .005
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lr_scheme: MultiStepLR
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niter: 400000
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warmup_iter: -1 # no warm up
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lr_steps: [15000, 50000, 100000, 200000]
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lr_gamma: 0.5
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pixel_criterion: l2
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pixel_weight: !!float 1e-2
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feature_criterion: l1
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feature_weight: .6
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feature_weight_decay: .98
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feature_weight_decay_steps: 1000
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feature_weight_minimum: .5
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gan_type: ragan # gan | ragan
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gan_weight: .1
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mega_batch_factor: 2
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swapout_G_freq: 113
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swapout_D_freq: 223
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swapout_duration: 40
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D_update_ratio: 1
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D_init_iters: -1
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manual_seed: 10
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val_freq: !!float 5e2
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#### logger
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logger:
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print_freq: 50
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save_checkpoint_freq: 500
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@ -1,106 +0,0 @@
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#### general settings
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name: train_vix_resgenv2
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use_tb_logger: true
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model: srgan
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distortion: sr
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scale: 4
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gpu_ids: [0]
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amp_opt_level: O1
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#### datasets
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datasets:
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train:
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name: vixcloseup
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mode: LQGT
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dataroot_GT: E:\4k6k\datasets\vixen\vix_tiled\hr
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dataroot_LQ: E:\4k6k\datasets\vixen\vix_tiled\lr
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use_flip: true
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use_rot: true
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doCrop: false
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use_shuffle: true
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n_workers: 4 # per GPU
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batch_size: 8
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target_size: 256
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color: RGB
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val:
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name: adrianna_val
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mode: LQGT
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dataroot_GT: E:\4k6k\datasets\adrianna\val\hhq
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dataroot_LQ: E:\4k6k\datasets\adrianna\val\hr
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|
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#### network structures
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network_G:
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||||
which_model_G: ResGenV2
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||||
nf: 256
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||||
nb_denoiser: 20
|
||||
nb_upsampler: 10
|
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upscale_applications: 2
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network_D:
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which_model_D: discriminator_resnet_passthrough
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nf: 64
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# LR corruption network.
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network_C:
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which_model_G: ResGenV2
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nf: 192
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nb_denoiser: 20
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nb_upsampler: 0
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upscale_applications: 0
|
||||
inject_noise: False
|
||||
|
||||
#### path
|
||||
path:
|
||||
pretrained_corruptors_dir: ../experiments/pretrained_corruptors
|
||||
#pretrain_model_G: ../experiments/pretrained_resnet_G.pth
|
||||
#pretrain_model_D: ~
|
||||
strict_load: true
|
||||
resume_state: ~
|
||||
|
||||
#### training settings: learning rate scheme, loss
|
||||
train:
|
||||
lr_G: !!float 1e-4
|
||||
weight_decay_G: 0
|
||||
beta1_G: 0.9
|
||||
beta2_G: 0.99
|
||||
lr_D: !!float 1e-4
|
||||
weight_decay_D: 0
|
||||
beta1_D: 0.9
|
||||
beta2_D: 0.99
|
||||
lr_scheme: MultiStepLR
|
||||
|
||||
niter: 400000
|
||||
warmup_iter: -1 # no warm up
|
||||
lr_steps: [20000, 60000, 80000, 100000]
|
||||
lr_gamma: 0.5
|
||||
mega_batch_factor: 2
|
||||
|
||||
swapout_G_freq: 113
|
||||
swapout_D_freq: 223
|
||||
swapout_duration: 40
|
||||
|
||||
corruptor_swapout_steps: 1000
|
||||
|
||||
pixel_criterion: l1
|
||||
pixel_weight: .01
|
||||
|
||||
feature_criterion: l1
|
||||
feature_weight: 1
|
||||
feature_weight_decay: 1
|
||||
feature_weight_decay_steps: 500
|
||||
feature_weight_minimum: 1
|
||||
|
||||
gan_type: ragan # gan | ragan
|
||||
gan_weight: .01
|
||||
|
||||
D_update_ratio: 1
|
||||
D_init_iters: 0
|
||||
D_noise_theta_init: .005 # Just fixed noise.
|
||||
D_noise_final_it: 1
|
||||
D_noise_theta_floor: .005
|
||||
|
||||
manual_seed: 10
|
||||
val_freq: !!float 5e2
|
||||
|
||||
#### logger
|
||||
logger:
|
||||
print_freq: 50
|
||||
save_checkpoint_freq: !!float 5e2
|
||||
Loading…
Reference in New Issue
Block a user