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AutoGL
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AutoGL/configs/nodeclf_sage_benchmark_smal...

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  1. ensemble:

  2.   name: null

  3. feature:

  4. - name: PYGNormalizeFeatures

  5. hpo:

  6.   max_evals: 10

  7.   name: random

  8. models:

  9. - hp_space:

  10.   - feasiblePoints: 2,3

  11.     parameterName: num_layers

  12.     type: DISCRETE

  13.   - cutFunc: lambda x:x[0] - 1

  14.     cutPara:

  15.     - num_layers

  16.     length: 2

  17.     maxValue:

  18.     - 16

  19.     - 64

  20.     minValue:

  21.     - 16

  22.     - 64

  23.     numericalType: INTEGER

  24.     parameterName: hidden

  25.     scalingType: LOG

  26.     type: NUMERICAL_LIST

  27.   - maxValue: 0.8

  28.     minValue: 0.2

  29.     parameterName: dropout

  30.     scalingType: LINEAR

  31.     type: DOUBLE

  32.   - feasiblePoints:

  33.     - mean

  34.     - add

  35.     - max

  36.     parameterName: agg

  37.     type: CATEGORICAL

  38.   - feasiblePoints:

  39.     - leaky_relu

  40.     - relu

  41.     - elu

  42.     - tanh

  43.     parameterName: act

  44.     type: CATEGORICAL

  45.   name: gcn

  46. trainer:

  47.   hp_space:

  48.   - maxValue: 300

  49.     minValue: 100

  50.     parameterName: max_epoch

  51.     scalingType: LINEAR

  52.     type: INTEGER

  53.   - maxValue: 30

  54.     minValue: 10

  55.     parameterName: early_stopping_round

  56.     scalingType: LINEAR

  57.     type: INTEGER

  58.   - maxValue: 0.05

  59.     minValue: 0.01

  60.     parameterName: lr

  61.     scalingType: LOG

  62.     type: DOUBLE

  63.   - maxValue: 0.001

  64.     minValue: 0.0001

  65.     parameterName: weight_decay

  66.     scalingType: LOG

  67.     type: DOUBLE