use_gpu: True
device: 2
early_stop:
  patience: 200
  improve_indicator_mode: mean
# monitoring: ['dissim']
federate:
  mode: standalone
  total_round_num: 400
data:
  root: data/
  type: 'csbm'
  #type: 'csbm_data_feb_05_2022-19:23'
  cSBM_phi: [0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8]
dataloader:
  type: pyg
model:
  type: gpr
  hidden: 256
  out_channels: 2
  task: node
personalization:
  local_param: ['prop1']
train:
  local_update_steps: 2
  optimizer:
    lr: 0.5
    weight_decay: 0.0005
    type: SGD
criterion:
  type: CrossEntropyLoss
trainer:
  type: nodeminibatch_trainer
finetune:
  local_update_steps: 2
eval:
  metrics: ['acc', 'correct']