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train_DRCT-L_SRx4_finetune_from_ImageNet_pretrain.yml
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train_DRCT-L_SRx4_finetune_from_ImageNet_pretrain.yml
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# general settings
name: train_DRCT-L_SRx4_finetune_from_ImageNet_pretrain
model_type: DRCTModel
scale: 4
num_gpu: auto
manual_seed: 0
# dataset and data loader settings
datasets:
train:
name: DF2K
type: PairedImageDataset
dataroot_gt: datasets/DF2K/DF2K_HR_sub
dataroot_lq: datasets/DF2K/DF2K_bicx4_sub
meta_info_file: drct/data/meta_info/meta_info_DF2Ksub_GT.txt
io_backend:
type: disk
gt_size: 256
use_hflip: true
use_rot: true
# data loader
use_shuffle: true
num_worker_per_gpu: 6
batch_size_per_gpu: 4
dataset_enlarge_ratio: 1
prefetch_mode: ~
val_1:
name: Set5
type: PairedImageDataset
dataroot_gt: ./datasets/Set5/GTmod4
dataroot_lq: ./datasets/Set5/LRbicx4
io_backend:
type: disk
val_2:
name: Set14
type: PairedImageDataset
dataroot_gt: ./datasets/Set14/GTmod4
dataroot_lq: ./datasets/Set14/LRbicx4
io_backend:
type: disk
# val_3:
# name: Urban100
# type: PairedImageDataset
# dataroot_gt: ./datasets/urban100/GTmod4
# dataroot_lq: ./datasets/urban100/LRbicx4
# io_backend:
# type: disk
# network structures
network_g:
type: DRCT
upscale: 4
in_chans: 3
img_size: 64
window_size: 16
compress_ratio: 3
squeeze_factor: 30
conv_scale: 0.01
overlap_ratio: 0.5
img_range: 1.
depths: [6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6]
embed_dim: 180
num_heads: [6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6]
mlp_ratio: 2
upsampler: 'pixelshuffle'
resi_connection: '1conv'
# path
path:
pretrain_network_g: ./experiments/train_DRCT-L_SRx4_ImageNet_from_scratch/models/net_g_latest.pth
param_key_g: 'params_ema'
strict_load_g: true
resume_state: ~
# training settings
train:
ema_decay: 0.999
optim_g:
type: Adam
lr: !!float 1e-5
weight_decay: 0
betas: [0.9, 0.99]
scheduler:
type: MultiStepLR
milestones: [125000, 200000, 225000, 240000]
gamma: 0.5
total_iter: 250000
warmup_iter: -1 # no warm up
# losses
pixel_opt:
type: L1Loss
loss_weight: 1.0
reduction: mean
# validation settings
val:
val_freq: !!float 5e3
save_img: false
pbar: False
metrics:
psnr:
type: calculate_psnr
crop_border: 4
test_y_channel: true
better: higher # the higher, the better. Default: higher
ssim:
type: calculate_ssim
crop_border: 4
test_y_channel: true
better: higher # the higher, the better. Default: higher
# logging settings
logger:
print_freq: 100
save_checkpoint_freq: !!float 5e3
use_tb_logger: true
wandb:
project: ~
resume_id: ~
# dist training settings
dist_params:
backend: nccl
port: 29500