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dmlc--dgl/dglgo/recipes/graphpred_pcba_gin.yaml
2026-07-13 13:35:51 +08:00

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YAML

version: 0.0.2
pipeline_name: graphpred
pipeline_mode: train
device: cuda:0 # Torch device name, e.q. cpu or cuda or cuda:0
data:
name: ogbg-molpcba
split_ratio: # Ratio to generate data split, for example set to [0.8, 0.1, 0.1] for 80% train/10% val/10% test. Leave blank to use builtin split in original dataset
model:
name: gin
embed_size: 300 # Embedding size.
num_layers: 5 # Number of layers.
dropout: 0.5 # Dropout rate.
virtual_node: true # Whether to use virtual node.
general_pipeline:
num_runs: 10 # Number of experiments to run
train_batch_size: 32 # Graph batch size when training
eval_batch_size: 32 # Graph batch size when evaluating
num_workers: 4 # Number of workers for data loading
optimizer:
name: Adam
lr: 0.001
weight_decay: 0
lr_scheduler:
name: StepLR
step_size: 100
gamma: 1
loss: BCEWithLogitsLoss
metric: average_precision_score
num_epochs: 100 # Number of training epochs
save_path: "results" # Directory to save the experiment results