PEMS_BAY_AutoSTG.yaml

---
sys:
  seed: 1

data:
  path: PEMS-BAY
  num_sensors: 325
  in_length: 12
  out_length: 12
  in_channels: 2
  out_channels: 1
  batch_size_per_gpu: 32
  train_prop: 0.7
  valid_prop: 0.1

model:
  name: PEMS_BAY_AutoSTG
  node_hiddens: [32,32]
  edge_hiddens: [32,32]
  hidden_channels: 32
  skip_channels: 256
  end_channels: 512
  layer_names: [STCell, ConvPooling, STCell, STCell, ConvPooling, STCell, STCell]
  num_mixed_ops: 6
  candidate_op_profiles: [
    [Zero, {

    }],
    [Identity, {

    }],
    [Conv, {
      type_name: fc,
      kernel_size: [1,1],
      stride: [1,1],
      padding: [0,0],
      dilation: [1,1],
      use_bn: True,
      dropout: 0
    }],
    [MetaConv, {
      type_name: tc,
      node_in_hidden: 32,
      meta_hiddens: [64,16,2],
      kernel_size: [1,3],
      stride: [1,1],
      padding: [0,1],
      dilation: [1,1],
      use_bn: True,
      dropout: 0
    }],
    [MetaGraphConv, {
      edge_in_hidden: 32,
      meta_hiddens: [64,16],
      num_graphs: 4,
      order: 2,
      use_bn: True,
      dropout: 0.2
    }],
  ]

trainer:
  arch_lr: 0.001
  arch_lr_decay_milestones: [50,60,70,80]
  arch_lr_decay_ratio: 0.1
  arch_decay: 0.00001
  arch_clip_gradient: 5
  
  weight_lr: 0.01
  weight_lr_decay_milestones: [50,60,70,80]
  weight_lr_decay_ratio: 0.1
  weight_decay: 0.00001
  weight_clip_gradient: 5

  num_search_iterations: 64
  num_search_arch_samples: 8
  num_train_iterations: 500

  criterion: 'masked_mae'
  metric_names: ['mae', 'rmse']
  metric_indexes: [2,5,11]
  print_frequency: 50