GraphGym/run/configs/example.yaml at master · laraque/GraphGym · GitHub

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# The recommended basic settings for GNN
out_dir: results
dataset:
  format: PyG
  name: Cora
  task: node
  task_type: classification
  transductive: True
  split: [0.8, 0.2]
  augment_feature: []
  augment_feature_dims: [0]
  augment_feature_repr: position
  augment_label: ''
  augment_label_dims: 0
  transform: none
train:
  batch_size: 32
  eval_period: 20
  ckpt_period: 100
model:
  type: gnn
  loss_fun: cross_entropy
  edge_decoding: dot
  graph_pooling: add
gnn:
  layers_pre_mp: 1
  layers_mp: 2
  layers_post_mp: 1
  dim_inner: 256
  layer_type: generalconv
  stage_type: stack
  batchnorm: True
  act: prelu
  dropout: 0.0
  agg: add
  normalize_adj: False
optim:
  optimizer: adam
  base_lr: 0.01
  max_epoch: 400