name: horse2zebra-CyCleGAN
engine: CyCleGAN
result_dir: ./result
max_pairs: 266800

misc:
  random_seed: 324

handler:
  clear_cuda_cache: False
  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: 2 # log image `image` times per epoch

model:
  generator:
    _type: CyCle-Generator
    in_channels: 3
    out_channels: 3
    base_channels: 64
    num_blocks: 9
    padding_mode: reflect
    norm_type: IN
  discriminator:
    _type: PatchDiscriminator
    in_channels: 3
    base_channels: 64

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: 0

optimizers:
  generator:
    _type: Adam
    lr: 2e-4
    betas: [ 0.5, 0.999 ]
  discriminator:
    _type: Adam
    lr: 2e-4
    betas: [ 0.5, 0.999 ]

data:
  train:
    scheduler:
      start_proportion: 0.5
      target_lr: 0
    buffer_size: 50
    dataloader:
      batch_size: 6
      shuffle: True
      num_workers: 2
      pin_memory: True
      drop_last: True
    dataset:
      _type: GenerationUnpairedDataset
      root_a: "/data/i2i/horse2zebra/trainA"
      root_b: "/data/i2i/horse2zebra/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:
    dataloader:
      batch_size: 4
      shuffle: False
      num_workers: 1
      pin_memory: False
      drop_last: False
    dataset:
      _type: GenerationUnpairedDataset
      root_a: "/data/i2i/horse2zebra/testA"
      root_b: "/data/i2i/horse2zebra/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 ]