DL-Art-School/codes/options/train/train_ESRGAN_blacked.yml

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#### general settings
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name: blacked_fix_and_upconv
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use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [0]
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amp_opt_level: O1
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#### datasets
datasets:
train:
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name: vixcloseup
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mode: LQGT
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dataroot_GT: K:\4k6k\4k_closeup\hr
dataroot_LQ: K:\4k6k\4k_closeup\lr_corrupted
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use_shuffle: true
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n_workers: 12 # per GPU
batch_size: 12
target_size: 256
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color: RGB
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
dataroot_LQ: E:\4k6k\datasets\adrianna\val\hr
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#### network structures
network_G:
which_model_G: RRDBNet
in_nc: 3
out_nc: 3
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nf: 48
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nb: 23
network_D:
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which_model_D: discriminator_resnet
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in_nc: 3
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nf: 48
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#### path
path:
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pretrain_model_G: ~
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strict_load: true
resume_state: ~
#### training settings: learning rate scheme, loss
train:
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lr_G: !!float 1e-4
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weight_decay_G: 0
beta1_G: 0.9
beta2_G: 0.99
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lr_D: !!float 2e-4
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weight_decay_D: 0
beta1_D: 0.9
beta2_D: 0.99
lr_scheme: MultiStepLR
niter: 400000
warmup_iter: -1 # no warm up
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lr_steps: [20000, 40000, 60000, 80000]
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lr_gamma: 0.5
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_criterion: l1
feature_weight: 1
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feature_weight_decay: .98
feature_weight_decay_steps: 500
feature_weight_minimum: .1
gan_type: gan # gan | ragan
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gan_weight: !!float 5e-3
D_update_ratio: 1
D_init_iters: 0
manual_seed: 10
val_freq: !!float 5e2
#### logger
logger:
print_freq: 50
save_checkpoint_freq: !!float 5e2