name: selfie2anime engine: U-GAT-IT result_dir: ./result max_pairs: 1000000 misc: random_seed: 324 handler: clear_cuda_cache: True set_epoch_for_dist_sampler: True checkpoint: epoch_interval: 1 # checkpoint once per `epoch_interval` epoch n_saved: 2 tensorboard: scalar: 100 # log scalar `scalar` times per epoch image: 4 # log image `image` times per epoch test: random: True images: 10 model: generator: _type: UGATIT-Generator _add_spectral_norm: True in_channels: 3 out_channels: 3 base_channels: 64 num_blocks: 4 img_size: 256 light: True local_discriminator: _type: UGATIT-Discriminator _add_spectral_norm: True in_channels: 3 base_channels: 64 num_blocks: 5 global_discriminator: _type: UGATIT-Discriminator _add_spectral_norm: True in_channels: 3 base_channels: 64 num_blocks: 7 loss: gan: loss_type: lsgan weight: 1.0 real_label_val: 1.0 fake_label_val: 0.0 cycle: level: 1 weight: 10.0 id: level: 1 weight: 10.0 cam: weight: 1000 mgc: weight: 0 optimizers: generator: _type: Adam lr: 0.0001 betas: [ 0.5, 0.999 ] weight_decay: 0.0001 discriminator: _type: Adam lr: 1e-4 betas: [ 0.5, 0.999 ] weight_decay: 0.0001 data: train: scheduler: start_proportion: 0.5 target_lr: 0 buffer_size: 50 dataloader: batch_size: 1 shuffle: True num_workers: 2 pin_memory: True drop_last: True dataset: _type: GenerationUnpairedDataset root_a: "/data/i2i/selfie2anime/trainA" root_b: "/data/i2i/selfie2anime/trainB" random_pair: True pipeline: - Load - Resize: size: [ 286, 286 ] - RandomCrop: size: [ 256, 256 ] - RandomHorizontalFlip - ToTensor - Normalize: mean: [ 0.5, 0.5, 0.5 ] std: [ 0.5, 0.5, 0.5 ] test: which: video_dataset dataloader: batch_size: 1 shuffle: False num_workers: 1 pin_memory: False drop_last: False dataset: _type: GenerationUnpairedDataset root_a: "/data/i2i/selfie2anime/testA" root_b: "/data/i2i/selfie2anime/testB" random_pair: False pipeline: - Load - Resize: size: [ 256, 256 ] - ToTensor - Normalize: mean: [ 0.5, 0.5, 0.5 ] std: [ 0.5, 0.5, 0.5 ] video_dataset: _type: SingleFolderDataset root: "/data/i2i/VoxCeleb2Anime/test_video_frames/" with_path: True pipeline: - Load - Resize: size: [ 256, 256 ] - ToTensor - Normalize: mean: [ 0.5, 0.5, 0.5 ] std: [ 0.5, 0.5, 0.5 ]