Takelapstyle_rev_first.yaml as an example.
| Field | Usage | Default |
|---|
| total_iters | total training steps | 30000 |
| min_max | numeric range of tensor（for image storage） | (0., 1.) |
| output_dir | path of the output | ./output_dir |
| snapshot_config: interval | interval for saving model parameters | 5000 |
| Field | Usage | Default |
|---|
| name | name of the model | LapStyleRevFirstModel |
| revnet_generator | set the revnet generator | RevisionNet |
| revnet_discriminator | set the revnet discriminator | LapStyleDiscriminator |
| draftnet_encode | set the draftnet encoder | Encoder |
| draftnet_decode | set the draftnet decoder | DecoderNet |
| calc_style_emd_loss | set the style loss 1 | CalcStyleEmdLoss |
| calc_content_relt_loss | set the content loss 1 | CalcContentReltLoss |
| calc_content_loss | set the content loss 2 | CalcContentLoss |
| calc_style_loss | set the style loss 2 | CalcStyleLoss |
| gan_criterion: name | set the GAN loss | GANLoss |
| gan_criterion: gan_mode | set the modal parameter of GAN loss | vanilla |
| content_layers | set the network layer that calculates content loss 2 | ['r11', 'r21', 'r31', 'r41', 'r51'] |
| style_layers | set the network layer that calculates style loss 2 | ['r11', 'r21', 'r31', 'r41', 'r51'] |
| content_weight | set the weight of total content loss | 1.0 |
| style_weigh | set the weight of total style loss | 3.0 |
| Field | Usage | Default |
|---|
| name | name of the dataset | LapStyleDataset |
| content_root | path of the dataset | data/coco/train2017/ |
| style_root | path of the target style image | data/starrynew.png |
| load_size | image size after resizing the input image | 280 |
| crop_size | image size after random cropping | 256 |
| num_workers | number of worker process | 16 |
| batch_size | size of the data sample for one training session | 5 |
| Field | Usage | Default |
|---|
| name | name of the learning strategy | NonLinearDecay |
| learning_rate | initial learning rate | 1e-4 |
| lr_decay | decay rate of the learning rate | 5e-5 |
| Field | Usage | Default |
|---|
| name | class name of the optimizer | Adam |
| net_names | the network under the optimizer | net_rev |
| beta1 | set beta1, parameter of the optimizer | 0.9 |
| beta2 | set beta2, parameter of the optimizer | 0.999 |
| Field | Usage | Default |
|---|
| interval | validation interval | 500 |
| save_img | whether to save image while validating | false |
| Field | Usage | Default |
|---|
| interval | log printing interval | 10 |
| visiual_interval | interval for saving the generated images during training | 500 |