DL-Art-School/codes/options/train/train_ESRGAN_res.yml
2020-05-06 17:25:48 -06:00

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YAML

#### general settings
name: esrgan_res
use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [0]
amp_opt_level: O1
#### datasets
datasets:
train:
name: DIV2K
mode: LQGT
dataroot_GT: E:/4k6k/datasets/div2k/DIV2K800_sub
dataroot_LQ: E:/4k6k/datasets/div2k/DIV2K800_sub_bicLRx4
use_shuffle: true
n_workers: 0 # per GPU
batch_size: 24
target_size: 128
use_flip: true
use_rot: true
color: RGB
val:
name: div2kval
mode: LQGT
dataroot_GT: E:/4k6k/datasets/div2k/div2k_valid_hr
dataroot_LQ: E:/4k6k/datasets/div2k/div2k_valid_lr_bicubic
#### network structures
network_G:
which_model_G: ResGen
nf: 256
nb_denoiser: 2
nb_upsampler: 28
network_D:
which_model_D: discriminator_resnet_passthrough
nf: 42
#### path
path:
#pretrain_model_G: ../experiments/blacked_fix_and_upconv_xl_part1/models/3000_G.pth
#pretrain_model_D: ~
strict_load: true
resume_state: ../experiments/esrgan_res/training_state/15500.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, 40000, 50000, 60000]
lr_gamma: 0.5
mega_batch_factor: 2
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_criterion: l1
feature_weight: 1
feature_weight_decay: 1
feature_weight_decay_steps: 500
feature_weight_minimum: 1
gan_type: gan # gan | ragan
gan_weight: !!float 1e-2
D_update_ratio: 2
D_init_iters: -1
manual_seed: 10
val_freq: !!float 5e2
#### logger
logger:
print_freq: 50
save_checkpoint_freq: !!float 5e2