configs/training/lama_small_train_masks.yaml

run_title: ''

training_model:
  kind: default
  visualize_each_iters: 1000
  concat_mask: true
  store_discr_outputs_for_vis: true

losses:
  l1:
    weight_missing: 0
    weight_known: 10
  perceptual:
    weight: 0
  adversarial:
    kind: r1
    weight: 10
    gp_coef: 0.001
    mask_as_fake_target: true
    allow_scale_mask: true
  feature_matching:
    weight: 100
  resnet_pl:
    weight: 30
    weights_path: ${env:TORCH_HOME}
optimizers:
  generator:
    kind: adam
    lr: 0.001
  discriminator:
    kind: adam
    lr: 0.0001
visualizer:
  key_order:
  - image
  - predicted_image
  - discr_output_fake
  - discr_output_real
  - inpainted
  rescale_keys:
  - discr_output_fake
  - discr_output_real
  kind: directory
  outdir: ./visualizer-output/lama-small-train-masks/samples

generator:
  kind: pix2pixhd_global
  input_nc: 4
  output_nc: 3
  ngf: 64
  n_downsampling: 3
  n_blocks: 9
  conv_kind: default
  add_out_act: sigmoid
discriminator:
  kind: pix2pixhd_nlayer
  input_nc: 3
  ndf: 64
  n_layers: 4

defaults:
  - location: docker
  - data: abl-04-256-mh-dist
  - evaluator: default_inpainted
  - trainer: any_gpu_large_ssim_ddp_final
  - hydra: overrides