{
  "task": "swinir_sr_lightweight_x2"     //  classical image sr for x2/x3/x4. root/task/images-models-options
  , "model": "plain" // "plain" | "plain2" if two inputs
  , "gpu_ids": [0,1,2,3,4,5,6,7]
  , "dist": true

  , "scale": 2       // 2 | 3 | 4
  , "n_channels": 3  // broadcast to "datasets", 1 for grayscale, 3 for color

  , "path": {
    "root": "superresolution"            // "denoising" | "superresolution" | "dejpeg"
    , "pretrained_netG": null      // path of pretrained model. We fine-tune X3/X4 models from X2 model, so that `G_optimizer_lr` and `G_scheduler_milestones` can be halved to save time.
    , "pretrained_netE": null      // path of pretrained model
  }

  , "datasets": {
    "train": {
      "name": "train_dataset"           // just name
      , "dataset_type": "sr"         // "dncnn" | "dnpatch" | "fdncnn" | "ffdnet" | "sr" | "srmd" | "dpsr" | "plain" | "plainpatch" | "jpeg"
      , "dataroot_H": "trainsets/trainH"// path of H training dataset. DIV2K (800 training images)
      , "dataroot_L": "trainsets/trainL"              // path of L training dataset

      , "H_size": 128                   // 128/192/256/512.

      , "dataloader_shuffle": true
      , "dataloader_num_workers": 16
      , "dataloader_batch_size": 64      // Total batch size =8x8=64 in SwinIR
    }
    , "test": {
      "name": "test_dataset"            // just name
      , "dataset_type": "sr"         // "dncnn" | "dnpatch" | "fdncnn" | "ffdnet" | "sr" | "srmd" | "dpsr" | "plain" | "plainpatch" | "jpeg"
      , "dataroot_H": "testsets/Set5/HR"  // path of H testing dataset
      , "dataroot_L": "testsets/Set5/LR_bicubic/X2"              // path of L testing dataset

    }
  }

  , "netG": {
    "net_type": "swinir" 
    , "upscale": 2                      // 2 | 3  | 4
    , "in_chans": 3 
    , "img_size": 64
    , "window_size": 8  
    , "img_range": 1.0 
    , "depths": [6, 6, 6, 6]
    , "embed_dim": 60 
    , "num_heads": [6, 6, 6, 6]
    , "mlp_ratio": 2 
    , "upsampler": "pixelshuffledirect"        // "pixelshuffle" | "pixelshuffledirect" | "nearest+conv" | null
    , "resi_connection": "1conv"        // "1conv" | "3conv"

    , "init_type": "default"
  }

  , "train": {
    "G_lossfn_type": "l1"               // "l1" preferred | "l2sum" | "l2" | "ssim" | "charbonnier"
    , "G_lossfn_weight": 1.0            // default

    , "E_decay": 0.999                  // Exponential Moving Average for netG: set 0 to disable; default setting 0.999

    , "G_optimizer_type": "adam"        // fixed, adam is enough
    , "G_optimizer_lr": 2e-4            // learning rate
    , "G_optimizer_wd": 0               // weight decay, default 0
    , "G_optimizer_clipgrad": null      // unused
    , "G_optimizer_reuse": true         // 

    , "G_scheduler_type": "MultiStepLR" // "MultiStepLR" is enough
    , "G_scheduler_milestones": [250000, 400000, 450000, 475000, 500000]
    , "G_scheduler_gamma": 0.5

    , "G_regularizer_orthstep": null    // unused
    , "G_regularizer_clipstep": null    // unused

    , "G_param_strict": true
    , "E_param_strict": true

    , "checkpoint_test": 5000           // for testing
    , "checkpoint_save": 5000           // for saving model
    , "checkpoint_print": 200           // for print
  }
}