Add pretraining config
Browse files
pretraining/HGNS_PreTrain_subnets_100.yaml
ADDED
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| 1 |
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callbacks:
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patience: 100
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tol: 0
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task:
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task_name: PreTraining
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data:
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baseMVA: 100
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mask_value: 0.0
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mask_p_high: 0.8
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mask_p_low: 0.1
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normalization: HeteroDataMVANormalizer
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training_networks: 100
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validation_networks:
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- subnet_case4619_goc_idx_1
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- subnet_case4837_goc_idx_2
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- subnet_case4917_goc_idx_1
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- subnet_case5658_epigrids_idx_3
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- subnet_case7336_epigrids_idx_6
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- subnet_case9591_goc_idx_4
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- subnet_case10480_goc_idx_7
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- subnet_case19402_goc_idx_3
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- subnet_case20758_epigrids_idx_3
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- subnet_case30000_goc_idx_2
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test_networks:
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- subnet_case4619_goc_idx_2
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- subnet_case4837_goc_idx_4
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- subnet_case4917_goc_idx_3
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- subnet_case5658_epigrids_idx_4
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- subnet_case7336_epigrids_idx_7
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- subnet_case9591_goc_idx_5
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- subnet_case10480_goc_idx_8
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- subnet_case19402_goc_idx_4
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- subnet_case20758_epigrids_idx_6
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- subnet_case30000_goc_idx_3
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workers: 16
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model:
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attention_head: 8
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edge_dim: 10
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hidden_size: 48
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input_bus_dim: 15
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input_gen_dim: 6
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output_bus_dim: 2
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output_gen_dim: 1
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num_layers: 12
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type: GNS_heterogeneous
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optimizer:
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beta1: 0.9
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beta2: 0.999
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learning_rate: 0.0005
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lr_decay: 0.7
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lr_patience: 5
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seed: 200
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training:
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batch_size: 32
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epochs: 300
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loss_weights:
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- 0.1
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- 0.1
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- 0.8
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losses:
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- LayeredWeightedPhysics
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- MaskedGenMSE
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- MaskedBusMSE
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loss_args:
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- base_weight: 0.5
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- {}
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- {}
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base_weight: 0.5
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accelerator: auto
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devices: auto
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strategy: auto
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verbose: true
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