env:
  debug: false
  cuda: true
  dist_backend: nccl
  matplotlib_mode: agg
  log_root_dir: log
  rnd_seed: 200

model: MODEL(sd_variation)
eval:
  main: lib.experiments.sd_default.eval
  stage: lib.experiments.sd_default.eval_stage_variation
  dataset: null
  save_code: true

  conditioning: 
    - assets/benz.jpg
    - assets/ghibli.jpg
    - assets/horse.png
    - assets/matisse.jpg
    - assets/penguin.png
    - assets/scream.jpg
    - assets/space.jpg
    - assets/vermeer.jpg
    - assets/boy_and_girl.jpg
    - assets/church.jpg
    - assets/firework.jpg
    - assets/house_by_lake.jpg
    - assets/night_light.jpg
    - assets/san_diego.jpg
    - assets/tiger.jpg
    - assets/train.jpg

  replicate: 1

  sample:
    output_dim: [512, 512]
    n_samples: 4
    ddim_steps: 50
    ddim_eta: 0.0
    scale: 7.5

  color_adj: true
  color_adj_keep_ratio: 0.5
  color_adj_simple: true

  batch_size_per_gpu: 0
  batch_size: null
  dataset_num_workers_per_gpu: 0
  dataset_num_workers: null

  pretrained_pth_ema: pretrained/sd-variation-ema.pth
  strict_sd: true

  is_lite: true
  fix_seed: true
  eval_subdir: sd_variation