cyclegan_horse2zebra.yaml

epochs: 200
isTrain: True
output_dir: output_dir
lambda_A: 10.0
lambda_B: 10.0
lambda_identity: 0.5

model:
  name: CycleGANModel
  defaults: &defaults
    norm_type: instance
    input_nc: 3
  generator:
    name: ResnetGenerator
    output_nc: 3
    n_blocks: 9
    ngf: 64
    use_dropout: False
    <<: *defaults
  discriminator:
    name: NLayerDiscriminator
    ndf: 64
    n_layers: 3
    <<: *defaults
  gan_mode: lsgan

dataset:
  train:
    name: UnpairedDataset
    dataroot: data/horse2zebra
    phase: train
    max_dataset_size: inf
    direction: AtoB
    input_nc: 3
    output_nc: 3
    serial_batches: False
    pool_size: 50
    transform:
      load_size: 286
      crop_size: 256
      preprocess: resize_and_crop
      no_flip: False
  test:
    name: SingleDataset
    dataroot: data/horse2zebra/testA
    max_dataset_size: inf
    direction: AtoB
    input_nc: 3
    output_nc: 3
    serial_batches: False
    pool_size: 50
    transform:
      load_size: 256
      crop_size: 256
      preprocess: resize_and_crop
      no_flip: True


optimizer:
  name: Adam
  beta1: 0.5
  lr_scheduler:
    name: linear
    learning_rate: 0.0002
    start_epoch: 100
    decay_epochs: 100

log_config:
  interval: 100
  visiual_interval: 500

snapshot_config:
  interval: 5