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File size: 1,421 Bytes
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model:
target: models.swinir.SwinIR
params:
img_size: 64
patch_size: 1
in_chans: 3
embed_dim: 180
depths: [6, 6, 6, 6, 6, 6, 6, 6]
num_heads: [6, 6, 6, 6, 6, 6, 6, 6]
window_size: 8
mlp_ratio: 2
sf: 8
img_range: 1.0
upsampler: "nearest+conv"
resi_connection: "1conv"
unshuffle: True
unshuffle_scale: 8
train:
lr: 1e-4
lr_min: 5e-6
batch: [16, 4] # batchsize for training and validation
microbatch: 2
num_workers: 8
prefetch_factor: 2
iterations: 800000
weight_decay: 0
save_freq: 20000
val_freq: 20000
log_freq: [100, 2000, 50]
data:
train:
type: gfpgan
params:
files_txt: ./datapipe/files_txt/ffhq512_train.txt
io_backend:
type: disk
use_hflip: true
mean: [0.0, 0.0, 0.0]
std: [1.0, 1.0, 1.0]
out_size: 512
blur_kernel_size: 41
kernel_list: ['iso', 'aniso']
kernel_prob: [0.5, 0.5]
blur_sigma: [0.1, 15]
downsample_range: [0.8, 32]
noise_range: [0, 20]
jpeg_range: [30, 100]
color_jitter_prob: ~
color_jitter_pt_prob: ~
gray_prob: 0.01
gt_gray: True
need_gt_path: False
val:
type: folder
params:
dir_path: /mnt/vdb/IRDiff/Face/testing_data/celeba512_lq
dir_path_gt: /mnt/vdb/IRDiff/Face/testing_data/celeba512_hq
ext: png
need_gt_path: False
length: ~
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