Add my own configs

This commit is contained in:
James Betker 2020-04-22 00:37:54 -06:00
parent af5dfaa90d
commit 2538ca9f33
4 changed files with 274 additions and 0 deletions

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name: RRDB_ESRGAN_x4
suffix: ~ # add suffix to saved images
model: sr
distortion: sr
scale: 4
crop_border: ~ # crop border when evaluation. If None(~), crop the scale pixels
gpu_ids: [0]
datasets:
test_1: # the 1st test dataset
name: set5
mode: LQ
dataroot_LQ: ../datasets/upsample_tests
#### network structures
network_G:
which_model_G: RRDBNet
in_nc: 3
out_nc: 3
nf: 64
nb: 23
upscale: 4
#### path
path:
pretrain_model_G: ../experiments/ESRGANx4_blacked_ft/models/31500_G.pth
pretrain_model_D: ../experiments/ESRGANx4_blacked_ft/models/31500_D.pth

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#### general settings
name: ESRGANx4_blacked_ft
use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [0]
amp_opt_level: O1
#### datasets
datasets:
train:
name: blacked
mode: LQGT
dataroot_GT: ../datasets/blacked/train/hr
dataroot_LQ: ../datasets/blacked/train/lr
use_shuffle: true
n_workers: 4 # per GPU
batch_size: 12
target_size: 256
use_flip: false
use_rot: false
color: RGB
val:
name: blacked_val
mode: LQGT
dataroot_GT: ../datasets/vrp/validation/hr
dataroot_LQ: ../datasets/vrp/validation/lr
#### network structures
network_G:
which_model_G: RRDBNet
in_nc: 3
out_nc: 3
nf: 64
nb: 23
network_D:
which_model_D: discriminator_vgg_128
in_nc: 3
nf: 64
#### path
path:
pretrain_model_G: ../experiments/ESRGANx4_blacked_ft/models/31500_G.pth
pretrain_model_D: ../experiments/ESRGANx4_blacked_ft/models/31500_D.pth
strict_load: true
resume_state: ../experiments/ESRGANx4_blacked_ft/training_state/31500.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: [10000, 30000, 50000, 70000]
lr_gamma: 0.5
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_criterion: l1
feature_weight: 1
gan_type: ragan # gan | ragan
gan_weight: !!float 1e-1
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

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#### general settings
name: ESRGANx4_VRP
use_tb_logger: true
model: srgan
distortion: sr
scale: 4
gpu_ids: [0]
#### datasets
datasets:
train:
name: VRP
mode: LQGT
dataroot_GT: ../datasets/vrp/train/hr
dataroot_LQ: ../datasets/vrp/train/lr
use_shuffle: true
n_workers: 0 # per GPU
batch_size: 16
target_size: 128
use_flip: true
use_rot: true
color: RGB
val:
name: VRP_val
mode: LQGT
dataroot_GT: ../datasets/vrp/validation/hr
dataroot_LQ: ../datasets/vrp/validation/lr
#### network structures
network_G:
which_model_G: RRDBNet
in_nc: 3
out_nc: 3
nf: 64
nb: 23
network_D:
which_model_D: discriminator_vgg_128
in_nc: 3
nf: 64
#### path
path:
pretrain_model_G: ../experiments/div2k_gen_pretrain.pth
pretrain_model_D: ../experiments/div2k_disc_pretrain.pth
strict_load: true
resume_state: ~
#### training settings: learning rate scheme, loss
train:
lr_G: !!float 1e-5
weight_decay_G: 0
beta1_G: 0.9
beta2_G: 0.99
lr_D: !!float 1e-5
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: [50000, 100000, 200000, 300000]
lr_gamma: 0.5
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_criterion: l1
feature_weight: 1
gan_type: ragan # gan | ragan
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

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#### general settings
name: downsample_GAN_blacked
use_tb_logger: true
model: srgan
distortion: sr
scale: .25
gpu_ids: [0]
amp_opt_level: O1
#### datasets
datasets:
train:
name: blacked
mode: GTLQ
dataroot_GT: ../datasets/blacked/train/hr
dataroot_LQ: ../datasets/lqprn/train/lr
use_shuffle: true
n_workers: 0 # per GPU
batch_size: 7
target_size: 64
use_flip: false
use_rot: false
color: RGB
val:
name: blacked_val
mode: LQGT
dataroot_GT: ../datasets/vrp/validation/hr
dataroot_LQ: ../datasets/vrp/validation/lr
#### network structures
network_G:
which_model_G: RRDBNet
in_nc: 3
out_nc: 3
nf: 64
nb: 23
network_D:
which_model_D: discriminator_vgg_128
in_nc: 3
nf: 64
#### path
path:
#pretrain_model_G: ../experiments/blacked_gen_20000_epochs.pth
#pretrain_model_D: ../experiments/blacked_disc_20000_epochs.pth
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: [10000, 30000, 50000, 70000]
lr_gamma: 0.5
pixel_criterion: l1
pixel_weight: !!float 1e-2
feature_weight: 0
gan_type: ragan # gan | ragan
gan_weight: 1
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