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| # 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 | |