91 lines
1.5 KiB
YAML
91 lines
1.5 KiB
YAML
data:
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type: 'PEMSD4'
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num_nodes: 307
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lag: 12
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horizon: 12
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val_ratio: 0.2
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test_ratio: 0.2
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tod: false
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normalizer: std
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column_wise: false
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default_graph: true
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add_time_in_day: true
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add_day_in_week: true
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steps_per_day: 288
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days_per_week: 7
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sample: 1
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input_dim: 3
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batch_size: 64
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model:
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type: 'STEP'
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dataset_name: 'PEMS04'
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input_dim: 1
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output_dim: 1
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num_nodes: 307
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lag: 12
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horizon: 12
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# TSFormer参数
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tsformer_args:
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patch_size: 12
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in_channel: 1
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embed_dim: 96
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num_heads: 4
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mlp_ratio: 4
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dropout: 0.1
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num_token: 4032
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mask_ratio: 0.75
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encoder_depth: 4
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decoder_depth: 1
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mode: "forecasting" # 预测模式
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# GraphWaveNet后端参数
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backend_args:
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num_nodes: 307
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support_len: 2
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dropout: 0.3
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gcn_bool: true
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addaptadj: true
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aptinit: null
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in_dim: 2
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out_dim: 12
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residual_channels: 32
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dilation_channels: 32
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skip_channels: 256
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end_channels: 512
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kernel_size: 2
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blocks: 4
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layers: 2
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# 离散图学习参数
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dgl_args:
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dataset_name: 'PEMS04'
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k: 10
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input_seq_len: 12
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output_seq_len: 12
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train:
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loss_func: mae
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seed: 10
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batch_size: 64
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epochs: 100
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lr_init: 0.002
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weight_decay: 1.0e-5
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lr_decay: true
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lr_decay_rate: 0.5
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lr_decay_step: "1,18,36,54,72"
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early_stop: true
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early_stop_patience: 15
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grad_norm: true
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max_grad_norm: 3.0
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real_value: true
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test:
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mae_thresh: null
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mape_thresh: 0.0
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log:
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log_step: 200
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plot: false
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