import path from 'path'

const name = 'pix2pix'
const cwd = process.env.PIX2PIX_CWD || path.join(process.env.HOME, 'code/' + name + '/')

const dataset = {
  type: 'pytorch',
  script: 'datasets/combine_A_and_B.py',
  params: (task) => {
  }
// python datasets/combine_A_and_B.py \
//   --fold_A /home/lens/Desktop/thumbs/woodscaled_4/A \
//   --fold_B /home/lens/Desktop/thumbs/woodscaled_4/B \
//   --fold_AB datasets/woodscaled_4/
}
const train = {
  type: 'pytorch',
  script: 'train.py',
  params: (task) => {
  },
// python train.py \
//    --dataroot "./datasets/$dataset" \
//    --name "$dataset" \
//    --model pix2pix  \
//    --loadSize 264 \
//    --fineSize 256 \
//    --which_model_netG unet_256  \
//    --which_direction AtoB  \
//    --lambda_B 100  \
//    --dataset_mode aligned  \
//    --epoch_count $epochs \
//    --which_epoch latest \
//    --continue_train \
//    --no_lsgan --norm batch --pool_size 0
}
const generate = {
  type: 'pytorch',
  script: 'generate.py',
  params: (task) => {
  },
}
const live = {
  type: 'pytorch',
  script: 'live-mogrify.py',
  params: (task) => {
  },
  // python live-mogrify.py \
  //   --dataroot "./sequences/$sequence" \
  //   --start_img "./sequences/$sequence/frame_00001.png" \
  //   --experiment "$checkpoint" \
  //   --name "$checkpoint" \
  //   --recursive --recursive-frac 0.1 \
  //   --sequence --sequence-frac 0.3 \
  //   --process-frac 0.5 \
  //   --transition \
  //   --transition-min 0.05 \
  //   --how_many 100000 --transition-period 1000 \
  //   --loadSize 256 --fineSize 256 \
  //   --just-copy --poll_delay 0.09 \
  //   --model test --which_model_netG unet_256  \
  //   --which_direction AtoB --dataset_mode recursive  \
  //   --which_epoch latest \
  //   --norm batch
}

export default {
  name, cwd,
  activities: {
    dataset, train, generate, live,
  }
}