xgboost-mnist-hpo.yaml

apiVersion: sagemaker.aws.amazon.com/v1
kind: HyperparameterTuningJob
metadata:
  name: xgboost-mnist-hpo
spec:
    hyperParameterTuningJobConfig:
        resourceLimits:
            maxNumberOfTrainingJobs: 10
            maxParallelTrainingJobs: 10
        strategy: "Bayesian"
    region: us-west-2
    tags:
      - key: test-key
        value: test-value
    hyperParameterTuningJobConfig:
      strategy: Bayesian
      hyperParameterTuningJobObjective:
        type: Minimize
        metricName: validation:error
      resourceLimits:
        maxNumberOfTrainingJobs: 11
        maxParallelTrainingJobs: 5
      parameterRanges:
        integerParameterRanges:
        - name: num_round
          minValue: '10'
          maxValue: '20'
          scalingType: Linear
        continuousParameterRanges: []
        categoricalParameterRanges: []
      trainingJobEarlyStoppingType: Auto
    trainingJobDefinition:
      staticHyperParameters:
        - name: base_score
          value: '0.5'
        - name: booster
          value: gbtree
        - name: csv_weights
          value: '0'
        - name: dsplit
          value: row
        - name: grow_policy
          value: depthwise
        - name: lambda_bias
          value: '0.0'
        - name: max_bin
          value: '256'
        - name: max_leaves
          value: '0'
        - name: normalize_type
          value: tree
        - name: objective
          value: reg:linear
        - name: one_drop
          value: '0'
        - name: prob_buffer_row
          value: '1.0'
        - name: process_type
          value: default
        - name: rate_drop
          value: '0.0'
        - name: refresh_leaf
          value: '1'
        - name: sample_type
          value: uniform
        - name: scale_pos_weight
          value: '1.0'
        - name: silent
          value: '0'
        - name: sketch_eps
          value: '0.03'
        - name: skip_drop
          value: '0.0'
        - name: tree_method
          value: auto
        - name: tweedie_variance_power
          value: '1.5'
        - name: updater
          value: grow_colmaker,prune
      algorithmSpecification:
        trainingImage: 433757028032.dkr.ecr.us-west-2.amazonaws.com/xgboost:1
        trainingInputMode: File
      roleArn: arn:aws:iam::123456789012:role/service-role/AmazonSageMaker-ExecutionRole
      inputDataConfig:
      - channelName: train
        dataSource:
          s3DataSource:
            s3DataType: S3Prefix
            s3Uri: https://s3-us-west-2.amazonaws.com/my-bucket/xgboost/train/
            s3DataDistributionType: FullyReplicated
        contentType: text/csv
        compressionType: None
        recordWrapperType: None
        inputMode: File
      - channelName: validation
        dataSource:
          s3DataSource:
            s3DataType: S3Prefix
            s3Uri: https://s3-us-west-2.amazonaws.com/my-bucket/xgboost/validation/
            s3DataDistributionType: FullyReplicated
        contentType: text/csv
        compressionType: None
        recordWrapperType: None
        inputMode: File
      outputDataConfig:
        s3OutputPath: https://s3-us-west-2.amazonaws.com/my-bucket/xgboost
      resourceConfig:
        instanceType: ml.m4.xlarge
        instanceCount: 1
        volumeSizeInGB: 25
      stoppingCondition:
        maxRuntimeInSeconds: 3600
      enableNetworkIsolation: true
      enableInterContainerTrafficEncryption: false