configs/train_1x-5x_INR_funsr.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: inr_diinn_select_scale_sr_warp
    args:
      scales: [2, 2.5, 3, 3.5, 4]
#      scales: [1.5, 1.7, 2, 2.3, 2.5, 2.7, 3, 3.3, 3.5, 3.7, 4, 4.3, 4.5, 4.7, 5]
      patch_size: 48
      augment: true
      val_mode: false
      test_mode: false
  batch_size: 8
  num_workers: 4

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: test
#      first_k: 128
      cache: none
  wrapper:
    name: cnn_fixed_scale_sr_warp
    args:
      scale_ratio: 2
      patch_size: 48
      augment: false
      val_mode: false
      test_mode: true
  batch_size: 4
  num_workers: 4

eval_type: psnr+ssim

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

model:
  name: funsr
  args:
    encoder_spec:
      name: edsr-baseline
#      name: rdn
#      name: rcan
      args:
        no_upsampling: true
    has_multiscale: true
    neck:
      name: transformer_neck
      args:
        d_dim: 256
        downsample: true
        has_pe: true
        has_norm: true
        class_token: true
        num_encoder_layers: 3
    decoder:
      name: sirens
      args:
        num_inner_layers: 9
        is_residual: true
    global_decoder:
      name: sirens
      is_proj: true
      args:
        num_inner_layers: 9
        is_residual: true
    encoder_rgb: true
    n_forward_times: 1
    encode_hr_coord: true
    has_bn: true
    encode_scale_ratio: true
    local_unfold: false
    weight_gen_func: 'nearest-exact'  # bilinear, nearest-exact,bicubic

optimizer:
  name: adamw
  args:
    lr: 0.0001
#optimizer:
#  name: adam
#  args:
#    lr: 0.0001

epoch_max: 4000

lr_scheduler:
#  name: CosineAnnealingLR
#  T_max: 1500
#  eta_min: 1.e-7
  name: CosineAnnealingWarmUpLR
  epochs: 4000
  warm_up_epochs: 50
  eta_min: 1.e-8

#  name: MultiStepLR
#  milestones: [2000, 3000]
#  gamma: 0.1

#resume: checkpoints/EXP20221215_00/epoch-last.pth
epoch_val_interval: 50
epoch_save_interval: 300