更新新数据集在其他模型下的配置

config/AGCRN/AirQuality.yaml

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+basic:
+  dataset: AirQuality
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  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:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 6
+  num_layers: 2
+  output_dim: 6
+  rnn_units: 64
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  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

config/AGCRN/BJTaxi-InFlow.yaml

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+basic:
+  dataset: BJTaxi-InFlow
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 1
+  num_layers: 2
+  output_dim: 1
+  rnn_units: 64
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/AGCRN/BJTaxi-OutFlow.yaml

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+basic:
+  dataset: BJTaxi-OutFlow
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 1
+  num_layers: 2
+  output_dim: 1
+  rnn_units: 64
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/AGCRN/METR-LA.yaml

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+basic:
+  dataset: METR-LA
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 207
+  steps_per_day: 288
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 1
+  num_layers: 2
+  output_dim: 1
+  rnn_units: 64
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 1000
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/AGCRN/NYCBike-InFlow.yaml

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+basic:
+  dataset: NYCBike-InFlow
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 1
+  num_layers: 2
+  output_dim: 1
+  rnn_units: 64
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/AGCRN/NYCBike-OutFlow.yaml

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+basic:
+  dataset: NYCBike-OutFlow
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cheb_k: 2
+  cheb_order: 2
+  embed_dim: 10
+  input_dim: 1
+  num_layers: 2
+  output_dim: 1
+  rnn_units: 64
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/AGCRN/SolarEnergy.yaml

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+basic:
+  dataset: SolarEnergy
+  device: cuda:0
+  mode: train
+  model: AGCRN
+  seed: 2023
+
+data:
+  batch_size: 64
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 137
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 64
+  dropout: 0.3
+  gcn_depth: 1
+  gcn_num: 2
+  hid_c: 64
+  in_dim: 1
+  num_nodes: 137
+  out_dim: 1
+  residual_channels: 32
+  skip_channels: 64
+  subgraph_size: 20
+  tanhalpha: 3
+  time_strides: 1
+
+train:
+  batch_size: 64
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 100
+  loss_func: mae
+  lr_decay: true
+  lr_decay_rate: 0.3
+  lr_decay_step: 5,20,40,70
+  lr_init: 0.003
+  mae_thresh:
+  mape_thresh: 0.001
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/DCRNN/AirQuality.yaml

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+basic:
+  dataset: AirQuality
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: true
+  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:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 6
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 6
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 100
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 6
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/BJTaxi-InFlow.yaml

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+basic:
+  dataset: BJTaxi-InFlow
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: true
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 1
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 100
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/BJTaxi-OutFlow.yaml

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+basic:
+  dataset: BJTaxi-OutFlow
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: true
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 1
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 100
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/METR-LA.yaml

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+basic:
+  dataset: METR-LA
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: true
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 207
+  steps_per_day: 288
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 1
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 1000
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/NYCBike-InFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: NYCBike-InFlow
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: true
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 1
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 100
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/NYCBike-OutFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: NYCBike-OutFlow
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: true
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  cl_decay_steps: 1000
+  filter_type: dual_random_walk
+  horizon: 24
+  input_dim: 1
+  l1_decay: 0
+  max_diffusion_step: 2
+  num_rnn_layers: 2
+  output_dim: 1
+  rnn_units: 64
+  seq_len: 24
+  use_curriculum_learning: true
+
+train:
+  batch_size: 32
+  debug: false
+  early_stop: true
+  early_stop_patience: 25
+  epochs: 300
+  grad_norm: true
+  log_step: 100
+  loss_func: mask_mae
+  lr_decay: true
+  lr_decay_rate: 0.1
+  lr_decay_step: 10,20,40,80
+  lr_init: 0.001
+  mae_thresh:
+  mape_thresh: 0.0
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: false
+  seed: 10
+  weight_decay: 0.0001

config/DCRNN/SolarEnergy.yaml

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+basic:
+  dataset: SolarEnergy
+  device: cuda:0
+  mode: train
+  model: DCRNN
+  seed: 2023
+
+data:
+  batch_size: 64
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 137
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 64
+  cl_decay_steps: 1000
+  filters: 64
+  gcn_depth: 2
+  in_dim: 1
+  kernel_size: 3
+  max_diffusion_step: 2
+  num_nodes: 137
+  num_rnn_layers: 2
+  num_units: 64
+  output_dim: 1
+  rnn_type: GRU
+
+train:
+  batch_size: 64
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 100
+  loss_func: mae
+  lr_decay: true
+  lr_decay_rate: 0.3
+  lr_decay_step: 5,20,40,70
+  lr_init: 0.003
+  mae_thresh:
+  mape_thresh: 0.001
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/AirQuality.yaml

@@ -0,0 +1,61 @@
+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

config/GWN/BJTaxi-InFlow.yaml

@@ -0,0 +1,61 @@
+basic:
+  dataset: BJTaxi-InFlow
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  addaptadj: true
+  aptinit:
+  batch_size: 32
+  blocks: 4
+  dilation_channels: 32
+  dropout: 0.3
+  end_channels: 512
+  gcn_bool: true
+  in_dim: 2
+  input_dim: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  residual_channels: 32
+  skip_channels: 256
+  supports:
+
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/BJTaxi-OutFlow.yaml

@@ -0,0 +1,61 @@
+basic:
+  dataset: BJTaxi-OutFlow
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  addaptadj: true
+  aptinit:
+  batch_size: 32
+  blocks: 4
+  dilation_channels: 32
+  dropout: 0.3
+  end_channels: 512
+  gcn_bool: true
+  in_dim: 2
+  input_dim: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  residual_channels: 32
+  skip_channels: 256
+  supports:
+
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/METR-LA.yaml

@@ -0,0 +1,61 @@
+basic:
+  dataset: METR-LA
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 207
+  steps_per_day: 288
+  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: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  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: 1000
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/NYCBike-InFlow.yaml

@@ -0,0 +1,61 @@
+basic:
+  dataset: NYCBike-InFlow
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  addaptadj: true
+  aptinit:
+  batch_size: 32
+  blocks: 4
+  dilation_channels: 32
+  dropout: 0.3
+  end_channels: 512
+  gcn_bool: true
+  in_dim: 2
+  input_dim: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  residual_channels: 32
+  skip_channels: 256
+  supports:
+
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/NYCBike-OutFlow.yaml

@@ -0,0 +1,61 @@
+basic:
+  dataset: NYCBike-OutFlow
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  addaptadj: true
+  aptinit:
+  batch_size: 32
+  blocks: 4
+  dilation_channels: 32
+  dropout: 0.3
+  end_channels: 512
+  gcn_bool: true
+  in_dim: 2
+  input_dim: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  residual_channels: 32
+  skip_channels: 256
+  supports:
+
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/GWN/SolarEnergy.yaml

@@ -0,0 +1,60 @@
+basic:
+  dataset: SolarEnergy
+  device: cuda:0
+  mode: train
+  model: GWN
+  seed: 2023
+
+data:
+  batch_size: 64
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 137
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  addaptadj: true
+  aptinit:
+  batch_size: 64
+  blocks: 4
+  dilation_channels: 32
+  dropout: 0.3
+  end_channels: 512
+  gcn_bool: true
+  in_dim: 2
+  input_dim: 1
+  kernel_size: 2
+  layers: 2
+  out_dim: 12
+  output_dim: 1
+  residual_channels: 32
+  skip_channels: 256
+  supports:
+
+train:
+  batch_size: 64
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 100
+  loss_func: mae
+  lr_decay: true
+  lr_decay_rate: 0.3
+  lr_decay_step: 5,20,40,70
+  lr_init: 0.003
+  mae_thresh:
+  mape_thresh: 0.001
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/AirQuality.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: AirQuality
+  device: cuda:0
+  mode: train
+  model: STGCN
+  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:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 6
+  n_his: 24
+  output_dim: 6
+  stblock_num: 2
+
+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

config/STGCN/BJTaxi-InFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: BJTaxi-InFlow
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/BJTaxi-OutFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: BJTaxi-OutFlow
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/METR-LA.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: METR-LA
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 207
+  steps_per_day: 288
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 300
+  grad_norm: false
+  log_step: 1000
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/NYCBike-InFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: NYCBike-InFlow
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/NYCBike-OutFlow.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: NYCBike-OutFlow
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/STGCN/SolarEnergy.yaml

@@ -0,0 +1,54 @@
+basic:
+  dataset: SolarEnergy
+  device: cuda:0
+  mode: train
+  model: STGCN
+  seed: 2023
+
+data:
+  batch_size: 64
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 137
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  Ks: 3
+  Kt: 3
+  act_func: glu
+  droprate: 0.5
+  enable_bias: true
+  graph_conv_type: cheb_graph_conv
+  gso_type: sym_norm_lap
+  input_dim: 1
+  n_his: 24
+  output_dim: 1
+  stblock_num: 2
+
+train:
+  batch_size: 64
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 100
+  loss_func: mae
+  lr_decay: true
+  lr_decay_rate: 0.3
+  lr_decay_step: 5,20,40,70
+  lr_init: 0.003
+  mae_thresh:
+  mape_thresh: 0.001
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/AirQuality.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: AirQuality
+  device: cuda:0
+  mode: train
+  model: TCN
+  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:
+  batch_size: 16
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 6
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 6
+
+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

config/TCN/BJTaxi-InFlow.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: BJTaxi-InFlow
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 32
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/BJTaxi-OutFlow.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: BJTaxi-OutFlow
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 1024
+  steps_per_day: 48
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 32
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/METR-LA.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: METR-LA
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 16
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 207
+  steps_per_day: 288
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 16
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 16
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 300
+  grad_norm: false
+  log_step: 1000
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/NYCBike-InFlow.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: NYCBike-InFlow
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 32
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/NYCBike-OutFlow.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: NYCBike-OutFlow
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 32
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 128
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 32
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 32
+  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: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0

config/TCN/SolarEnergy.yaml

@@ -0,0 +1,50 @@
+basic:
+  dataset: SolarEnergy
+  device: cuda:0
+  mode: train
+  model: TCN
+  seed: 2023
+
+data:
+  batch_size: 64
+  column_wise: false
+  days_per_week: 7
+  horizon: 24
+  input_dim: 1
+  lag: 24
+  normalizer: std
+  num_nodes: 137
+  steps_per_day: 24
+  test_ratio: 0.2
+  val_ratio: 0.2
+
+model:
+  batch_size: 64
+  dropout: 0.2
+  hidden_channels: [32, 64, 32]
+  input_dim: 1
+  kernel_size: 3
+  num_layers: 3
+  output_dim: 1
+
+train:
+  batch_size: 64
+  debug: false
+  early_stop: true
+  early_stop_patience: 15
+  epochs: 100
+  grad_norm: false
+  log_step: 100
+  loss_func: mae
+  lr_decay: true
+  lr_decay_rate: 0.3
+  lr_decay_step: 5,20,40,70
+  lr_init: 0.003
+  mae_thresh:
+  mape_thresh: 0.001
+  max_grad_norm: 5
+  output_dim: 1
+  plot: false
+  real_value: true
+  seed: 10
+  weight_decay: 0