name: huawei-TSIT-1
engine: GauGAN
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: TSIT-Generator
    _add_spectral_norm: True
    in_channels: 3
    out_channels: 3
    num_blocks: 7
#  discriminator:
#    _type: MultiScaleDiscriminator
#    _add_spectral_norm: True
#    num_scale: 2
#    down_sample_method: "bilinear"
#    discriminator_cfg:
#      _type: PatchDiscriminator
#      in_channels: 3
#      base_channels: 64
#      num_conv: 4
#      need_intermediate_feature: True
  discriminator:
    _type: PatchDiscriminator
    _add_spectral_norm: True
    in_channels: 3
    base_channels: 64
    num_conv: 4
    need_intermediate_feature: True


loss:
  gan:
    loss_type: hinge
    weight: 1.0
    real_label_val: 1
    fake_label_val: 0.0
  perceptual:
    layer_weights:
      "1": 0.03125
      "6": 0.0625
      "11": 0.125
      "20": 0.25
      "29": 1
    criterion: 'L1'
    style_loss: False
    perceptual_loss: True
    weight: 1
  mgc:
    weight: 5
  fm:
    weight: 1
  edge:
    weight: 0
    hed_pretrained_model_path: ./network-bsds500.pytorch

optimizers:
  generator:
    _type: Adam
    lr: 1e-4
    betas: [ 0, 0.9 ]
    weight_decay: 0.0001
  discriminator:
    _type: Adam
    lr: 4e-4
    betas: [ 0, 0.9 ]
    weight_decay: 0.0001

data:
  train:
    scheduler:
      start_proportion: 0.5
      target_lr: 0
    buffer_size: 0
    dataloader:
      batch_size: 1
      shuffle: True
      num_workers: 2
      pin_memory: True
      drop_last: True
    dataset:
      _type: GenerationUnpairedDataset
      root_a: "/data/face2cartoon/all_face"
      root_b: "/data/selfie2anime/trainB/"
      random_pair: True
      pipeline_a:
        - Load
        - RandomCrop:
            size: [ 178, 178 ]
        - Resize:
            size: [ 256, 256 ]
        - RandomHorizontalFlip
        - ToTensor
        - Normalize:
            mean: [ 0.5, 0.5, 0.5 ]
            std: [ 0.5, 0.5, 0.5 ]
      pipeline_b:
        - 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/face2cartoon/test/human"
      root_b: "/data/face2cartoon/test/anime"
      random_pair: True
      pipeline_a:
        - Load
        - Resize:
            size: [ 256, 256 ]
        - ToTensor
        - Normalize:
            mean: [ 0.5, 0.5, 0.5 ]
            std: [ 0.5, 0.5, 0.5 ]
      pipeline_b:
        - 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 ]