DL-Art-School/codes/options/train/train_vix_resgenv2.yml

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#### general settings
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name: train_vix_resgenv2
use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [0]
amp_opt_level: O1
#### datasets
datasets:
train:
name: vixcloseup
mode: LQGT
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dataroot_GT: E:\4k6k\datasets\vixen\4k_closeup\hr
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dataroot_LQ: E:\4k6k\datasets\vixen\4k_closeup\lr_corrupted
doCrop: false
use_shuffle: true
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n_workers: 0 # per GPU
batch_size: 8
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target_size: 192
color: RGB
val:
name: adrianna_val
mode: LQGT
dataroot_GT: E:\4k6k\datasets\adrianna\val\hhq
dataroot_LQ: E:\4k6k\datasets\adrianna\val\hr
#### network structures
network_G:
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which_model_G: ResGenV2
nf: 256
nb_denoiser: 20
nb_upsampler: 10
upscale_applications: 0
network_D:
which_model_D: discriminator_resnet_passthrough
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nf: 64
# LR corruption network.
network_C:
which_model_G: ResGenV2
nf: 192
nb_denoiser: 20
nb_upsampler: 0
upscale_applications: 0
inject_noise: False
#### path
path:
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#pretrain_model_G: ../experiments/pretrained_resnet_G.pth
#pretrain_model_D: ~
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pretrain_model_C: ../experiments/pretrained_corruptors/resgen_xl_noise_19000.pth
strict_load: true
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resume_state: ~
#### training settings: learning rate scheme, loss
train:
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lr_G: !!float 1e-4
weight_decay_G: 0
beta1_G: 0.9
beta2_G: 0.99
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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
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lr_steps: [20000, 60000, 80000, 100000]
lr_gamma: 0.5
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mega_batch_factor: 2
pixel_criterion: l1
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pixel_weight: .01
feature_criterion: l1
feature_weight: 1
feature_weight_decay: 1
feature_weight_decay_steps: 500
feature_weight_minimum: 1
gan_type: gan # gan | ragan
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gan_weight: .01
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D_update_ratio: 1
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D_init_iters: 0
manual_seed: 10
val_freq: !!float 5e2
#### logger
logger:
print_freq: 50
save_checkpoint_freq: !!float 5e2