basic:
  dataset: AirQuality
  device: cuda:0
  mode: train
  model: GWN
  seed: 2023

data:
  batch_size: 16
  column_wise: false
  days_per_week: 7
  horizon: 24
  input_dim: 6
  lag: 24
  normalizer: std
  num_nodes: 35
  steps_per_day: 24
  test_ratio: 0.2
  val_ratio: 0.2

model:
  addaptadj: true
  aptinit:
  batch_size: 16
  blocks: 4
  dilation_channels: 32
  dropout: 0.3
  end_channels: 512
  gcn_bool: true
  in_dim: 2
  input_dim: 6
  kernel_size: 2
  layers: 2
  out_dim: 12
  output_dim: 6
  residual_channels: 32
  skip_channels: 256
  supports:


train:
  batch_size: 16
  debug: false
  early_stop: true
  early_stop_patience: 15
  epochs: 300
  grad_norm: false
  log_step: 100
  loss_func: mae
  lr_decay: false
  lr_decay_rate: 0.3
  lr_decay_step: 5,20,40,70
  lr_init: 0.003
  mae_thresh:
  mape_thresh: 0.0
  max_grad_norm: 5
  output_dim: 6
  plot: false
  real_value: true
  seed: 10
  weight_decay: 0