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2 Commits
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e50f443470
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e50f443470 | |
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c4414dd5d9 |
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@ -0,0 +1,54 @@
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basic:
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dataset: PEMS-BAY
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device: cuda:0
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mode: train
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model: AEPSA_v2
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seed: 2023
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data:
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||||||
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batch_size: 16
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column_wise: false
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||||||
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days_per_week: 7
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horizon: 24
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input_dim: 1
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||||||
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lag: 24
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||||||
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normalizer: std
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||||||
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num_nodes: 325
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||||||
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steps_per_day: 288
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test_ratio: 0.2
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val_ratio: 0.2
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model:
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||||||
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d_ff: 128
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d_model: 64
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dropout: 0.2
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gpt_layers: 9
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gpt_path: ./GPT-2
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input_dim: 1
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||||||
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n_heads: 1
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||||||
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num_nodes: 325
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||||||
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patch_len: 6
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||||||
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pred_len: 24
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seq_len: 24
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stride: 7
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word_num: 1000
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train:
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batch_size: 16
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debug: false
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early_stop: true
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||||||
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early_stop_patience: 15
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epochs: 100
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grad_norm: false
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||||||
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log_step: 100
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loss_func: mae
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||||||
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lr_decay: true
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||||||
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lr_decay_rate: 0.3
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lr_decay_step: 5,20,40,70
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||||||
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lr_init: 0.003
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||||||
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mae_thresh: None
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||||||
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mape_thresh: 0.001
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||||||
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max_grad_norm: 5
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||||||
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output_dim: 1
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||||||
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plot: false
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||||||
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weight_decay: 0
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||||||
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@ -5,11 +5,11 @@ basic:
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||||||
model: TWDGCN
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model: TWDGCN
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seed: 2023
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seed: 2023
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data:
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data:
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batch_size: 16
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batch_size: 64
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||||||
column_wise: false
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column_wise: false
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||||||
days_per_week: 7
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days_per_week: 7
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||||||
horizon: 24
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horizon: 24
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||||||
input_dim: 6
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input_dim: 1
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||||||
lag: 24
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lag: 24
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||||||
normalizer: std
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normalizer: std
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||||||
num_nodes: 35
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num_nodes: 35
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||||||
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@ -19,14 +19,16 @@ data:
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model:
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model:
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cheb_order: 2
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cheb_order: 2
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embed_dim: 12
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embed_dim: 12
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input_dim: 6
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horizon: 24
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||||||
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
output_dim: 6
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num_nodes: 35
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||||||
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
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||||||
use_day: true
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use_day: true
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||||||
use_week: false
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use_week: false
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||||||
train:
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train:
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batch_size: 16
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batch_size: 64
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debug: false
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debug: false
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||||||
early_stop: true
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early_stop: true
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early_stop_patience: 15
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early_stop_patience: 15
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@ -38,10 +40,10 @@ train:
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lr_decay_rate: 0.3
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lr_decay_rate: 0.3
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lr_decay_step: 5,20,40,70
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lr_decay_step: 5,20,40,70
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lr_init: 0.003
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lr_init: 0.003
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||||||
mae_thresh: ''
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mae_thresh: 0.001
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mape_thresh: 0.0
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mape_thresh: 0.0
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max_grad_norm: 5
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max_grad_norm: 5
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output_dim: 6
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output_dim: 1
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plot: false
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plot: false
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real_value: true
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real_value: true
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seed: 10
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seed: 10
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@ -19,8 +19,10 @@ data:
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model:
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model:
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cheb_order: 2
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cheb_order: 2
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embed_dim: 12
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embed_dim: 12
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horizon: 24
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input_dim: 1
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input_dim: 1
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num_layers: 1
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num_layers: 1
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num_nodes: 1024
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output_dim: 1
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output_dim: 1
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rnn_units: 64
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rnn_units: 64
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use_day: true
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use_day: true
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@ -38,7 +40,7 @@ train:
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lr_decay_rate: 0.3
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lr_decay_rate: 0.3
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lr_decay_step: 5,20,40,70
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lr_decay_step: 5,20,40,70
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lr_init: 0.003
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lr_init: 0.003
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||||||
mae_thresh: ''
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mae_thresh: 0.0
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||||||
mape_thresh: 0.0
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mape_thresh: 0.0
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||||||
max_grad_norm: 5
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max_grad_norm: 5
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||||||
output_dim: 1
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output_dim: 1
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||||||
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|
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||||||
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@ -19,8 +19,10 @@ data:
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||||||
model:
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model:
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cheb_order: 2
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cheb_order: 2
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embed_dim: 12
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embed_dim: 12
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||||||
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horizon: 24
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||||||
input_dim: 1
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
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num_nodes: 1024
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
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||||||
use_day: true
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use_day: true
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||||||
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|
@ -38,7 +40,7 @@ train:
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||||||
lr_decay_rate: 0.3
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lr_decay_rate: 0.3
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||||||
lr_decay_step: 5,20,40,70
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lr_decay_step: 5,20,40,70
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||||||
lr_init: 0.003
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lr_init: 0.003
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||||||
mae_thresh: ''
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mae_thresh: 0.0
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||||||
mape_thresh: 0.0
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mape_thresh: 0.0
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||||||
max_grad_norm: 5
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max_grad_norm: 5
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||||||
output_dim: 1
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output_dim: 1
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||||||
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|
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||||||
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@ -25,6 +25,7 @@ model:
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||||||
horizon: 12
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horizon: 12
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||||||
input_dim: 1
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
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num_nodes: 13
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 32
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rnn_units: 32
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||||||
use_day: true
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use_day: true
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||||||
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|
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||||||
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@ -8,9 +8,9 @@ data:
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||||||
batch_size: 16
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batch_size: 16
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||||||
column_wise: false
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column_wise: false
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||||||
days_per_week: 7
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days_per_week: 7
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||||||
horizon: 12
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horizon: 24
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||||||
input_dim: 1
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input_dim: 1
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||||||
lag: 12
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lag: 24
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||||||
normalizer: std
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normalizer: std
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||||||
num_nodes: 207
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num_nodes: 207
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||||||
steps_per_day: 288
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steps_per_day: 288
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||||||
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@ -19,8 +19,10 @@ data:
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||||||
model:
|
model:
|
||||||
cheb_order: 2
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cheb_order: 2
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||||||
embed_dim: 12
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embed_dim: 12
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||||||
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horizon: 24
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||||||
input_dim: 1
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
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num_nodes: 207
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
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||||||
use_day: true
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use_day: true
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||||||
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|
@ -38,7 +40,7 @@ train:
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||||||
lr_decay_rate: 0.3
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lr_decay_rate: 0.3
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||||||
lr_decay_step: 5,20,40,70
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lr_decay_step: 5,20,40,70
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||||||
lr_init: 0.003
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lr_init: 0.003
|
||||||
mae_thresh: ''
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mae_thresh: 0.0
|
||||||
mape_thresh: 0.0
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mape_thresh: 0.0
|
||||||
max_grad_norm: 5
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max_grad_norm: 5
|
||||||
output_dim: 1
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output_dim: 1
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||||||
|
|
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||||||
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@ -8,19 +8,21 @@ data:
|
||||||
batch_size: 32
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batch_size: 32
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||||||
column_wise: false
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column_wise: false
|
||||||
days_per_week: 7
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days_per_week: 7
|
||||||
horizon: 24
|
horizon: 12
|
||||||
input_dim: 1
|
input_dim: 1
|
||||||
lag: 24
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lag: 12
|
||||||
normalizer: std
|
normalizer: std
|
||||||
num_nodes: 1024
|
num_nodes: 128
|
||||||
steps_per_day: 48
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steps_per_day: 48
|
||||||
test_ratio: 0.2
|
test_ratio: 0.2
|
||||||
val_ratio: 0.2
|
val_ratio: 0.2
|
||||||
model:
|
model:
|
||||||
cheb_order: 2
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cheb_order: 2
|
||||||
embed_dim: 12
|
embed_dim: 12
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||||||
|
horizon: 12
|
||||||
input_dim: 1
|
input_dim: 1
|
||||||
num_layers: 1
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num_layers: 1
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||||||
|
num_nodes: 128
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||||||
output_dim: 1
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output_dim: 1
|
||||||
rnn_units: 64
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rnn_units: 64
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||||||
use_day: true
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use_day: true
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||||||
|
|
@ -38,8 +40,8 @@ train:
|
||||||
lr_decay_rate: 0.3
|
lr_decay_rate: 0.3
|
||||||
lr_decay_step: 5,20,40,70
|
lr_decay_step: 5,20,40,70
|
||||||
lr_init: 0.003
|
lr_init: 0.003
|
||||||
mae_thresh: ''
|
mae_thresh: 0.0
|
||||||
mape_thresh: 0.0
|
mape_thresh: 0.001
|
||||||
max_grad_norm: 5
|
max_grad_norm: 5
|
||||||
output_dim: 1
|
output_dim: 1
|
||||||
plot: false
|
plot: false
|
||||||
|
|
|
||||||
|
|
@ -8,19 +8,21 @@ data:
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||||||
batch_size: 32
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batch_size: 32
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||||||
column_wise: false
|
column_wise: false
|
||||||
days_per_week: 7
|
days_per_week: 7
|
||||||
horizon: 24
|
horizon: 12
|
||||||
input_dim: 1
|
input_dim: 1
|
||||||
lag: 24
|
lag: 12
|
||||||
normalizer: std
|
normalizer: std
|
||||||
num_nodes: 1024
|
num_nodes: 128
|
||||||
steps_per_day: 48
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steps_per_day: 48
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||||||
test_ratio: 0.2
|
test_ratio: 0.2
|
||||||
val_ratio: 0.2
|
val_ratio: 0.2
|
||||||
model:
|
model:
|
||||||
cheb_order: 2
|
cheb_order: 2
|
||||||
embed_dim: 12
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embed_dim: 12
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||||||
|
horizon: 12
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||||||
input_dim: 1
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
|
num_nodes: 128
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
|
||||||
use_day: true
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use_day: true
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||||||
|
|
@ -38,8 +40,8 @@ train:
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||||||
lr_decay_rate: 0.3
|
lr_decay_rate: 0.3
|
||||||
lr_decay_step: 5,20,40,70
|
lr_decay_step: 5,20,40,70
|
||||||
lr_init: 0.003
|
lr_init: 0.003
|
||||||
mae_thresh: ''
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mae_thresh: 0.0
|
||||||
mape_thresh: 0.0
|
mape_thresh: 0.001
|
||||||
max_grad_norm: 5
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max_grad_norm: 5
|
||||||
output_dim: 1
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output_dim: 1
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||||||
plot: false
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plot: false
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||||||
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|
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||||||
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@ -21,8 +21,10 @@ data:
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||||||
model:
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model:
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||||||
cheb_order: 2
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cheb_order: 2
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||||||
embed_dim: 12
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embed_dim: 12
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||||||
|
horizon: 12
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||||||
input_dim: 1
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input_dim: 1
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||||||
num_layers: 1
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num_layers: 1
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||||||
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num_nodes: 358
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
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||||||
use_day: true
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use_day: true
|
||||||
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|
|
||||||
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@ -21,8 +21,10 @@ data:
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||||||
model:
|
model:
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||||||
cheb_order: 2
|
cheb_order: 2
|
||||||
embed_dim: 12
|
embed_dim: 12
|
||||||
|
horizon: 12
|
||||||
input_dim: 1
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input_dim: 1
|
||||||
num_layers: 1
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num_layers: 1
|
||||||
|
num_nodes: 307
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||||||
output_dim: 1
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output_dim: 1
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||||||
rnn_units: 64
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rnn_units: 64
|
||||||
use_day: true
|
use_day: true
|
||||||
|
|
@ -41,8 +43,8 @@ train:
|
||||||
lr_decay_rate: 0.3
|
lr_decay_rate: 0.3
|
||||||
lr_decay_step: 5,20,40,70
|
lr_decay_step: 5,20,40,70
|
||||||
lr_init: 0.003
|
lr_init: 0.003
|
||||||
mae_thresh:
|
mae_thresh: 0.0
|
||||||
mape_thresh: 0.0
|
mape_thresh: 0.001
|
||||||
max_grad_norm: 5
|
max_grad_norm: 5
|
||||||
output_dim: 1
|
output_dim: 1
|
||||||
plot: false
|
plot: false
|
||||||
|
|
|
||||||
|
|
@ -21,8 +21,10 @@ data:
|
||||||
model:
|
model:
|
||||||
cheb_order: 2
|
cheb_order: 2
|
||||||
embed_dim: 12
|
embed_dim: 12
|
||||||
|
horizon: 12
|
||||||
input_dim: 1
|
input_dim: 1
|
||||||
num_layers: 1
|
num_layers: 1
|
||||||
|
num_nodes: 883
|
||||||
output_dim: 1
|
output_dim: 1
|
||||||
rnn_units: 64
|
rnn_units: 64
|
||||||
use_day: true
|
use_day: true
|
||||||
|
|
|
||||||
|
|
@ -21,8 +21,10 @@ data:
|
||||||
model:
|
model:
|
||||||
cheb_order: 2
|
cheb_order: 2
|
||||||
embed_dim: 12
|
embed_dim: 12
|
||||||
|
horizon: 12
|
||||||
input_dim: 1
|
input_dim: 1
|
||||||
num_layers: 1
|
num_layers: 1
|
||||||
|
num_nodes: 170
|
||||||
output_dim: 1
|
output_dim: 1
|
||||||
rnn_units: 64
|
rnn_units: 64
|
||||||
use_day: true
|
use_day: true
|
||||||
|
|
|
||||||
|
|
@ -5,11 +5,11 @@ basic:
|
||||||
model: TWDGCN
|
model: TWDGCN
|
||||||
seed: 2023
|
seed: 2023
|
||||||
data:
|
data:
|
||||||
batch_size: 16
|
batch_size: 64
|
||||||
column_wise: false
|
column_wise: false
|
||||||
days_per_week: 7
|
days_per_week: 7
|
||||||
horizon: 24
|
horizon: 24
|
||||||
input_dim: 137
|
input_dim: 1
|
||||||
lag: 24
|
lag: 24
|
||||||
normalizer: std
|
normalizer: std
|
||||||
num_nodes: 137
|
num_nodes: 137
|
||||||
|
|
@ -19,14 +19,16 @@ data:
|
||||||
model:
|
model:
|
||||||
cheb_order: 2
|
cheb_order: 2
|
||||||
embed_dim: 12
|
embed_dim: 12
|
||||||
input_dim: 137
|
horizon: 24
|
||||||
|
input_dim: 1
|
||||||
num_layers: 1
|
num_layers: 1
|
||||||
output_dim: 137
|
num_nodes: 137
|
||||||
|
output_dim: 1
|
||||||
rnn_units: 64
|
rnn_units: 64
|
||||||
use_day: true
|
use_day: true
|
||||||
use_week: false
|
use_week: false
|
||||||
train:
|
train:
|
||||||
batch_size: 16
|
batch_size: 64
|
||||||
debug: false
|
debug: false
|
||||||
early_stop: true
|
early_stop: true
|
||||||
early_stop_patience: 15
|
early_stop_patience: 15
|
||||||
|
|
@ -38,10 +40,10 @@ train:
|
||||||
lr_decay_rate: 0.3
|
lr_decay_rate: 0.3
|
||||||
lr_decay_step: 5,20,40,70
|
lr_decay_step: 5,20,40,70
|
||||||
lr_init: 0.003
|
lr_init: 0.003
|
||||||
mae_thresh: ''
|
mae_thresh: 0.0
|
||||||
mape_thresh: 0.0
|
mape_thresh: 0.001
|
||||||
max_grad_norm: 5
|
max_grad_norm: 5
|
||||||
output_dim: 137
|
output_dim: 1
|
||||||
plot: false
|
plot: false
|
||||||
real_value: true
|
real_value: true
|
||||||
seed: 10
|
seed: 10
|
||||||
|
|
|
||||||
|
|
@ -89,7 +89,6 @@ class TWDGCN(nn.Module):
|
||||||
self.num_layers = args["num_layers"]
|
self.num_layers = args["num_layers"]
|
||||||
self.use_day = args["use_day"]
|
self.use_day = args["use_day"]
|
||||||
self.use_week = args["use_week"]
|
self.use_week = args["use_week"]
|
||||||
self.default_graph = args["default_graph"]
|
|
||||||
|
|
||||||
self.node_embeddings1 = nn.Parameter(
|
self.node_embeddings1 = nn.Parameter(
|
||||||
torch.randn(self.num_node, args["embed_dim"]), requires_grad=True
|
torch.randn(self.num_node, args["embed_dim"]), requires_grad=True
|
||||||
|
|
@ -154,17 +153,17 @@ class TWDGCN(nn.Module):
|
||||||
node_embedding1 = self.node_embeddings1
|
node_embedding1 = self.node_embeddings1
|
||||||
|
|
||||||
if self.use_day:
|
if self.use_day:
|
||||||
t_i_d_data = source[..., 1]
|
t_i_d_data = source[..., -2]
|
||||||
T_i_D_emb = self.T_i_D_emb[(t_i_d_data * 288).long()]
|
T_i_D_emb = self.T_i_D_emb[(t_i_d_data * 288).long()]
|
||||||
node_embedding1 = node_embedding1 * T_i_D_emb
|
node_embedding1 = node_embedding1 * T_i_D_emb
|
||||||
|
|
||||||
if self.use_week:
|
if self.use_week:
|
||||||
d_i_w_data = source[..., 2]
|
d_i_w_data = source[..., -1]
|
||||||
D_i_W_emb = self.D_i_W_emb[d_i_w_data.long()]
|
D_i_W_emb = self.D_i_W_emb[d_i_w_data.long()]
|
||||||
node_embedding1 = node_embedding1 * D_i_W_emb
|
node_embedding1 = node_embedding1 * D_i_W_emb
|
||||||
|
|
||||||
node_embeddings = [node_embedding1, self.node_embeddings1]
|
node_embeddings = [node_embedding1, self.node_embeddings1]
|
||||||
source = source[..., 0].unsqueeze(-1)
|
source = source[..., 0:self.input_dim]
|
||||||
|
|
||||||
init_state1 = self.encoder1.init_hidden(source.shape[0])
|
init_state1 = self.encoder1.init_hidden(source.shape[0])
|
||||||
output, _ = self.encoder1(source, init_state1, node_embeddings)
|
output, _ = self.encoder1(source, init_state1, node_embeddings)
|
||||||
|
|
|
||||||
264
test_results.txt
264
test_results.txt
|
|
@ -734,270 +734,6 @@ Traceback (most recent call last):
|
||||||
AttributeError: 'NoneType' object has no attribute 'to'
|
AttributeError: 'NoneType' object has no attribute 'to'
|
||||||
```
|
```
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/NYCBike-InFlow.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD4.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/METR-LA.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/AirQuality.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/NYCBike-OutFlow.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD8.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD7(L).yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD3.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/SolarEnergy.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/Hainan.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD7.yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/TWDGCN/PEMSD7(M).yaml
|
|
||||||
|
|
||||||
```
|
|
||||||
|
|
||||||
Traceback (most recent call last):
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 66, in <module>
|
|
||||||
main()
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/run.py", line 19, in main
|
|
||||||
model = init.init_model(args)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/utils/initializer.py", line 14, in init_model
|
|
||||||
model = model_selector(args).to(device)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/model_selector.py", line 38, in model_selector
|
|
||||||
return TWDGCN(model_config)
|
|
||||||
^^^^^^^^^^^^^^^^^^^^
|
|
||||||
File "/user/czzhangheng/code/TrafficWheel/model/TWDGCN/TWDGCN.py", line 84, in __init__
|
|
||||||
self.num_node = args["num_nodes"]
|
|
||||||
~~~~^^^^^^^^^^^^^
|
|
||||||
KeyError: 'num_nodes'
|
|
||||||
```
|
|
||||||
|
|
||||||
#### /user/czzhangheng/code/TrafficWheel/config/STSGCN/NYCBike-InFlow.yaml
|
#### /user/czzhangheng/code/TrafficWheel/config/STSGCN/NYCBike-InFlow.yaml
|
||||||
|
|
||||||
```
|
```
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue