dmlc--dgl
Hongzhi (Steve), Chen
0b9df9d798
Co-authored-by: Steve <ubuntu@ip-172-31-34-29.ap-northeast-1.compute.internal>
41 行
866 B
Python
41 行
866 B
Python
"""Best hyperparameters found."""
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import torch
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MWE_GCN_proteins = {
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"num_ew_channels": 8,
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"num_epochs": 2000,
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"in_feats": 1,
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"hidden_feats": 10,
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"out_feats": 112,
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"n_layers": 3,
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"lr": 2e-2,
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"weight_decay": 0,
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"patience": 1000,
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"dropout": 0.2,
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"aggr_mode": "sum", ## 'sum' or 'concat' for the aggregation across channels
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"ewnorm": "both",
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}
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MWE_DGCN_proteins = {
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"num_ew_channels": 8,
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"num_epochs": 2000,
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"in_feats": 1,
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"hidden_feats": 10,
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"out_feats": 112,
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"n_layers": 2,
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"lr": 1e-2,
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"weight_decay": 0,
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"patience": 300,
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"dropout": 0.5,
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"aggr_mode": "sum",
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"residual": True,
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"ewnorm": "none",
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}
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def get_exp_configure(args):
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if args["model"] == "MWE-GCN":
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return MWE_GCN_proteins
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elif args["model"] == "MWE-DGCN":
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return MWE_DGCN_proteins
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