ml-engine-config-hypertune.yaml

trainingInput:
  scaleTier: CUSTOM
  masterType: complex_model_m
  workerType: complex_model_m
  parameterServerType: large_model
  workerCount: 4
  parameterServerCount: 2
  hyperparameters:
      goal: MAXIMIZE
      hyperparameterMetricTag: MAP_with_Leaked_Clicks
      maxTrials: 30
      maxParallelTrials: 1
      params:
        - parameterName: train_batch_size
          type: DISCRETE
          discreteValues: [64, 128, 256, 512]          
        - parameterName: linear_l1_regularization
          type: DISCRETE
          discreteValues: [0.01, 0.03, 0.1, 0.3, 1.0, 3.0]   
        - parameterName: linear_l2_regularization
          type: DISCRETE
          discreteValues: [0.0, 0.01, 0.03, 0.1, 0.3, 1.0, 10.0, 30.0]
        - parameterName: linear_learning_rate
          type: DISCRETE
          discreteValues: [0.01, 0.05, 0.1, 0.2]
        - parameterName: deep_l1_regularization
          type: DISCRETE
          discreteValues: [0.01, 0.03, 0.1, 0.3, 1.0, 3.0]   
        - parameterName: deep_l2_regularization
          type: DISCRETE
          discreteValues: [0.01, 0.03, 0.1, 0.3, 1.0]
        - parameterName: deep_dropout
          type: DISCRETE
          discreteValues: [0.0, 0.1, 0.2, 0.3]
        - parameterName: deep_learning_rate
          type: DISCRETE
          discreteValues: [0.01, 0.05, 0.1, 0.2]
        - parameterName: deep_embedding_size_factor
          type: DISCRETE
          discreteValues: [2,4,6,8,10]
        - parameterName: deep_hidden_units
          type: CATEGORICAL
          categoricalValues: ["512 256 128", "512 512 512", "1024 512 256", "1024 1024 1024"]