configs/train_CNN.yaml

train_dataset:
  dataset:
    name: hr_data_loader
    args:
#      root_path: /data/kyanchen/datasets/UC/256
#      split_file: data_split/UC_split.json
      root_path: /data/kyanchen/datasets/AID
      split_file: data_split/AID_split.json
      split_key: train
      cache: none
  wrapper:
    name: cnn_fixed_scale_sr_warp
    args:
      scale_ratio: 2
      patch_size: 48
      augment: true
      val_mode: false
      test_mode: false
  batch_size: 96
  num_workers: 8

val_dataset:
  dataset:
    name: hr_data_loader
    args:
#      root_path: /data/kyanchen/datasets/UC/256
#      split_file: data_split/UC_split.json
      root_path: /data/kyanchen/datasets/AID
      split_file: data_split/AID_split.json
      split_key: val
      cache: none
  wrapper:
    name: cnn_fixed_scale_sr_warp
    args:
      scale_ratio: 2
      patch_size: 48
      augment: false
      val_mode: true
      test_mode: false
  batch_size: 32
  num_workers: 4

data_norm:
  img: {sub: [0.5], div: [0.5]}
  gt: {sub: [0.5], div: [0.5]}

#model:
#  name: TransENet
#  args:
#    scale_ratio: 2

#model:
#  name: SRCNN
#  args:
#    scale_ratio: 2

#model:
#  name: FSRCNN
#  args:
#    scale_ratio: 2

#model:
#  name: LGCNET
#  args:
#    scale_ratio: 2

#model:
#  name: DCM
#  args:
#    scale_ratio: 2

model:
  name: VDSR
  args:
    scale_ratio: 2

optimizer:
  name: adamw
  args:
    lr: 0.0001

epoch_max: 1300
#epoch_max: 2000

lr_scheduler:
#  name: CosineAnnealingLR
#  T_max: 300
#  eta_min: 1.e-6
  name: MultiStepLR
  milestones: [1000]
  gamma: 0.5

epoch_val_interval: 50
epoch_save_interval: 300