configs/config.yaml

# data parameters
dataset_name: imagenet
data_with_subfolder: True
train_data_path: /media/ouc/4T_A/datasets/ImageNet/ILSVRC2012_img_train/
val_data_path:
resume:
batch_size: 48
image_shape: [256, 256, 3]
mask_shape: [128, 128]
mask_batch_same: True
max_delta_shape: [32, 32]
margin: [0, 0]
discounted_mask: True
spatial_discounting_gamma: 0.9
random_crop: True
mask_type: hole     # hole | mosaic
mosaic_unit_size: 12

# training parameters
expname: benchmark
cuda: False
gpu_ids: [0, 1, 2]    # set the GPU ids to use, e.g. [0] or [1, 2]
num_workers: 4
lr: 0.0001
beta1: 0.5
beta2: 0.9
n_critic: 5
niter: 500000
print_iter: 100
viz_iter: 1000
viz_max_out: 16
snapshot_save_iter: 5000

# loss weight
coarse_l1_alpha: 1.2
l1_loss_alpha: 1.2
ae_loss_alpha: 1.2
global_wgan_loss_alpha: 1.
gan_loss_alpha: 0.001
wgan_gp_lambda: 10

# network parameters
netG:
  input_dim: 3
  ngf: 32

netD:
  input_dim: 3
  ndf: 64