# How often do you want to log the training stats. | |
# network_list: | |
# gen: gen_optimizer | |
# dis: dis_optimizer | |
distributed: False | |
image_to_tensorboard: True | |
snapshot_save_iter: 40000 | |
snapshot_save_epoch: 20 | |
snapshot_save_start_iter: 20000 | |
snapshot_save_start_epoch: 10 | |
image_save_iter: 1000 | |
max_epoch: 200 | |
logging_iter: 100 | |
results_dir: ./eval_results | |
gen_optimizer: | |
type: adam | |
lr: 0.0001 | |
adam_beta1: 0.5 | |
adam_beta2: 0.999 | |
lr_policy: | |
iteration_mode: True | |
type: step | |
step_size: 300000 | |
gamma: 0.2 | |
trainer: | |
type: trainers.face_trainer::FaceTrainer | |
pretrain_warp_iteration: 200000 | |
loss_weight: | |
weight_perceptual_warp: 2.5 | |
weight_perceptual_final: 4 | |
vgg_param_warp: | |
network: vgg19 | |
layers: ['relu_1_1', 'relu_2_1', 'relu_3_1', 'relu_4_1', 'relu_5_1'] | |
use_style_loss: False | |
num_scales: 4 | |
vgg_param_final: | |
network: vgg19 | |
layers: ['relu_1_1', 'relu_2_1', 'relu_3_1', 'relu_4_1', 'relu_5_1'] | |
use_style_loss: True | |
num_scales: 4 | |
style_to_perceptual: 250 | |
init: | |
type: 'normal' | |
gain: 0.02 | |
gen: | |
type: generators.face_model::FaceGenerator | |
param: | |
mapping_net: | |
coeff_nc: 73 | |
descriptor_nc: 256 | |
layer: 3 | |
warpping_net: | |
encoder_layer: 5 | |
decoder_layer: 3 | |
base_nc: 32 | |
editing_net: | |
layer: 3 | |
num_res_blocks: 2 | |
base_nc: 64 | |
common: | |
image_nc: 3 | |
descriptor_nc: 256 | |
max_nc: 256 | |
use_spect: False | |
# Data options. | |
data: | |
type: data.vox_dataset::VoxDataset | |
path: ./dataset/vox_lmdb | |
resolution: 256 | |
semantic_radius: 13 | |
train: | |
batch_size: 5 | |
distributed: True | |
val: | |
batch_size: 8 | |
distributed: True | |