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data:
image_size: 64
channels: 3
num_workers: 2
train_data_dir: '/data/JGW/hsguan/JGWNET/train/' # path to directory of train data
test_data_dir: '/data/JGW/hsguan/JGWNET/selected/' # path to directory of test data
#test_data_dir: '/home/dachuang/hsguan/JGWNET/data2/test2/'
#test_save_dir: '/home/dachuang/hsguan/JGWNET/selected' # path to directory of saving restored data
test_save_dir: '/home/dachuang/hsguan/JGWNET/result90'
val_save_dir: '/data/JGW/hsguan/validation/'
grid_r: 16
conditional: True
tensorboard: '/home/dachuang/hsguan/JGWNET/90logs'
model:
in_channels: 3
out_ch: 3
ch: 128
ch_mult: [1, 2, 3, 4]
num_res_blocks: 2
attn_resolutions: [16, ]
dropout: 0.0
ema_rate: 0.999
ema: True
resamp_with_conv: True
diffusion:
beta_schedule: linear
beta_start: 0.0001
beta_end: 0.02
num_diffusion_timesteps: 1000
training:
patch_n: 8
batch_size: 8
n_epochs: 1000
n_iters: 2000000
snapshot_freq: 20 # model save frequency
validation_freq: 10000
resume: './diffusion_model_new' # path to pretrained model
seed: 61 # random seed
sampling:
batch_size: 1
last_only: True
sampling_timesteps: 100
optim:
weight_decay: 0.01
optimizer: "Adam"
lr: 0.0001
amsgrad: False
eps: 0.00000001
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