total_iters: 1000000
output_dir: output_dir
# tensor range for function tensor2img
min_max:
  (0., 1.)

model:
  name: BaseSRModel
  generator:
    name: RRDBNet
    in_nc: 3
    out_nc: 3
    nf: 64
    nb: 23
  pixel_criterion:
    name: L1Loss

dataset:
  train:
    name: SRDataset
    gt_folder: data/DIV2K/DIV2K_train_HR_sub
    lq_folder: data/DIV2K/DIV2K_train_LR_bicubic/X4_sub
    num_workers: 4
    batch_size: 16
    scale: 4
    preprocess:
      - name: LoadImageFromFile
        key: lq
      - name: LoadImageFromFile
        key: gt
      - name: Transforms
        input_keys: [lq, gt]
        pipeline:
          - name: SRPairedRandomCrop
            gt_patch_size: 128
            scale: 4
            keys: [image, image]
          - name: PairedRandomHorizontalFlip
            keys: [image, image]
          - name: PairedRandomVerticalFlip
            keys: [image, image]
          - name: PairedRandomTransposeHW
            keys: [image, image]
          - name: Transpose
            keys: [image, image]
          - name: Normalize
            mean: [0., .0, 0.]
            std: [255., 255., 255.]
            keys: [image, image]
  test:
    name: SRDataset
    gt_folder: data/DIV2K/val_set14/Set14
    lq_folder: data/DIV2K/val_set14/Set14_bicLRx4
    scale: 4
    preprocess:
      - name: LoadImageFromFile
        key: lq
      - name: LoadImageFromFile
        key: gt
      - name: Transforms
        input_keys: [lq, gt]
        pipeline:
          - name: Transpose
            keys: [image, image]
          - name: Normalize
            mean: [0., .0, 0.]
            std: [255., 255., 255.]
            keys: [image, image]

lr_scheduler:
  name: CosineAnnealingRestartLR
  learning_rate: 0.0002
  periods: [250000, 250000, 250000, 250000]
  restart_weights: [1, 1, 1, 1]
  eta_min: !!float 1e-7

optimizer:
  name: Adam
  # add parameters of net_name to optim
  # name should in self.nets
  net_names:
    - generator
  beta1: 0.9
  beta2: 0.99

validate:
  interval: 5000
  save_img: false

  metrics:
    psnr: # metric name, can be arbitrary
      name: PSNR
      crop_border: 4
      test_y_channel: false
    ssim:
      name: SSIM
      crop_border: 4
      test_y_channel: false

log_config:
  interval: 10
  visiual_interval: 500

snapshot_config:
  interval: 5000