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Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

google-native.ml/v1.Study

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Google Cloud Native is in preview. Google Cloud Classic is fully supported.

Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
pulumi/pulumi-google-native

    Creates a study. Auto-naming is currently not supported for this resource.

    Create Study Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new Study(name: string, args: StudyArgs, opts?: CustomResourceOptions);
    @overload
def Study(resource_name: str,
          args: StudyArgs,
          opts: Optional[ResourceOptions] = None)

@overload
def Study(resource_name: str,
          opts: Optional[ResourceOptions] = None,
          study_config: Optional[GoogleCloudMlV1__StudyConfigArgs] = None,
          study_id: Optional[str] = None,
          location: Optional[str] = None,
          project: Optional[str] = None)
    func NewStudy(ctx *Context, name string, args StudyArgs, opts ...ResourceOption) (*Study, error)
    public Study(string name, StudyArgs args, CustomResourceOptions? opts = null)
    public Study(String name, StudyArgs args)
public Study(String name, StudyArgs args, CustomResourceOptions options)

    type: google-native:ml/v1:Study
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args StudyArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args StudyArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args StudyArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args StudyArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args StudyArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Example

    The following reference example uses placeholder values for all input properties.

    var examplestudyResourceResourceFromMlv1 = new GoogleNative.Ml.V1.Study("examplestudyResourceResourceFromMlv1", new()
{
    StudyConfig = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1__StudyConfigArgs
    {
        Parameters = new[]
        {
            new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfig_ParameterSpecArgs
            {
                Parameter = "string",
                Type = GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_ParameterSpecType.ParameterTypeUnspecified,
                CategoricalValueSpec = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs
                {
                    Values = new[]
                    {
                        "string",
                    },
                },
                ChildParameterSpecs = new[]
                {
                    googleCloudMlV1_StudyConfig_ParameterSpec,
                },
                DiscreteValueSpec = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs
                {
                    Values = new[]
                    {
                        0,
                    },
                },
                DoubleValueSpec = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs
                {
                    MaxValue = 0,
                    MinValue = 0,
                },
                IntegerValueSpec = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs
                {
                    MaxValue = "string",
                    MinValue = "string",
                },
                ParentCategoricalValues = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs
                {
                    Values = new[]
                    {
                        "string",
                    },
                },
                ParentDiscreteValues = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs
                {
                    Values = new[]
                    {
                        0,
                    },
                },
                ParentIntValues = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs
                {
                    Values = new[]
                    {
                        "string",
                    },
                },
                ScaleType = GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType.ScaleTypeUnspecified,
            },
        },
        Algorithm = GoogleNative.Ml.V1.GoogleCloudMlV1__StudyConfigAlgorithm.AlgorithmUnspecified,
        AutomatedStoppingConfig = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1__AutomatedStoppingConfigArgs
        {
            DecayCurveStoppingConfig = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs
            {
                UseElapsedTime = false,
            },
            MedianAutomatedStoppingConfig = new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs
            {
                UseElapsedTime = false,
            },
        },
        Metrics = new[]
        {
            new GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfig_MetricSpecArgs
            {
                Goal = GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_MetricSpecGoal.GoalTypeUnspecified,
                Metric = "string",
            },
        },
    },
    StudyId = "string",
    Location = "string",
    Project = "string",
});

    example, err := ml.NewStudy(ctx, "examplestudyResourceResourceFromMlv1", &ml.StudyArgs{
StudyConfig: &ml.GoogleCloudMlV1__StudyConfigArgs{
Parameters: []ml.GoogleCloudMlV1_StudyConfig_ParameterSpecArgs{
{
Parameter: pulumi.String("string"),
Type: ml.GoogleCloudMlV1_StudyConfig_ParameterSpecTypeParameterTypeUnspecified,
CategoricalValueSpec: {
Values: pulumi.StringArray{
pulumi.String("string"),
},
},
ChildParameterSpecs: ml.GoogleCloudMlV1_StudyConfig_ParameterSpecArray{
googleCloudMlV1_StudyConfig_ParameterSpec,
},
DiscreteValueSpec: {
Values: pulumi.Float64Array{
pulumi.Float64(0),
},
},
DoubleValueSpec: {
MaxValue: pulumi.Float64(0),
MinValue: pulumi.Float64(0),
},
IntegerValueSpec: {
MaxValue: pulumi.String("string"),
MinValue: pulumi.String("string"),
},
ParentCategoricalValues: {
Values: pulumi.StringArray{
pulumi.String("string"),
},
},
ParentDiscreteValues: {
Values: pulumi.Float64Array{
pulumi.Float64(0),
},
},
ParentIntValues: {
Values: pulumi.StringArray{
pulumi.String("string"),
},
},
ScaleType: ml.GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeScaleTypeUnspecified,
},
},
Algorithm: ml.GoogleCloudMlV1__StudyConfigAlgorithmAlgorithmUnspecified,
AutomatedStoppingConfig: &ml.GoogleCloudMlV1__AutomatedStoppingConfigArgs{
DecayCurveStoppingConfig: &ml.GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs{
UseElapsedTime: pulumi.Bool(false),
},
MedianAutomatedStoppingConfig: &ml.GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs{
UseElapsedTime: pulumi.Bool(false),
},
},
Metrics: ml.GoogleCloudMlV1_StudyConfig_MetricSpecArray{
&ml.GoogleCloudMlV1_StudyConfig_MetricSpecArgs{
Goal: ml.GoogleCloudMlV1_StudyConfig_MetricSpecGoalGoalTypeUnspecified,
Metric: pulumi.String("string"),
},
},
},
StudyId: pulumi.String("string"),
Location: pulumi.String("string"),
Project: pulumi.String("string"),
})

    var examplestudyResourceResourceFromMlv1 = new Study("examplestudyResourceResourceFromMlv1", StudyArgs.builder()        
    .studyConfig(GoogleCloudMlV1__StudyConfigArgs.builder()
        .parameters(GoogleCloudMlV1_StudyConfig_ParameterSpecArgs.builder()
            .parameter("string")
            .type("PARAMETER_TYPE_UNSPECIFIED")
            .categoricalValueSpec(GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs.builder()
                .values("string")
                .build())
            .childParameterSpecs(googleCloudMlV1_StudyConfig_ParameterSpec)
            .discreteValueSpec(GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs.builder()
                .values(0)
                .build())
            .doubleValueSpec(GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs.builder()
                .maxValue(0)
                .minValue(0)
                .build())
            .integerValueSpec(GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs.builder()
                .maxValue("string")
                .minValue("string")
                .build())
            .parentCategoricalValues(GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs.builder()
                .values("string")
                .build())
            .parentDiscreteValues(GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs.builder()
                .values(0)
                .build())
            .parentIntValues(GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs.builder()
                .values("string")
                .build())
            .scaleType("SCALE_TYPE_UNSPECIFIED")
            .build())
        .algorithm("ALGORITHM_UNSPECIFIED")
        .automatedStoppingConfig(GoogleCloudMlV1__AutomatedStoppingConfigArgs.builder()
            .decayCurveStoppingConfig(GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs.builder()
                .useElapsedTime(false)
                .build())
            .medianAutomatedStoppingConfig(GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs.builder()
                .useElapsedTime(false)
                .build())
            .build())
        .metrics(GoogleCloudMlV1_StudyConfig_MetricSpecArgs.builder()
            .goal("GOAL_TYPE_UNSPECIFIED")
            .metric("string")
            .build())
        .build())
    .studyId("string")
    .location("string")
    .project("string")
    .build());

    examplestudy_resource_resource_from_mlv1 = google_native.ml.v1.Study("examplestudyResourceResourceFromMlv1",
    study_config=google_native.ml.v1.GoogleCloudMlV1__StudyConfigArgs(
        parameters=[google_native.ml.v1.GoogleCloudMlV1_StudyConfig_ParameterSpecArgs(
            parameter="string",
            type=google_native.ml.v1.GoogleCloudMlV1_StudyConfig_ParameterSpecType.PARAMETER_TYPE_UNSPECIFIED,
            categorical_value_spec=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs(
                values=["string"],
            ),
            child_parameter_specs=[google_cloud_ml_v1__study_config__parameter_spec],
            discrete_value_spec=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs(
                values=[0],
            ),
            double_value_spec=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs(
                max_value=0,
                min_value=0,
            ),
            integer_value_spec=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs(
                max_value="string",
                min_value="string",
            ),
            parent_categorical_values=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs(
                values=["string"],
            ),
            parent_discrete_values=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs(
                values=[0],
            ),
            parent_int_values=google_native.ml.v1.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs(
                values=["string"],
            ),
            scale_type=google_native.ml.v1.GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType.SCALE_TYPE_UNSPECIFIED,
        )],
        algorithm=google_native.ml.v1.GoogleCloudMlV1__StudyConfigAlgorithm.ALGORITHM_UNSPECIFIED,
        automated_stopping_config=google_native.ml.v1.GoogleCloudMlV1__AutomatedStoppingConfigArgs(
            decay_curve_stopping_config=google_native.ml.v1.GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs(
                use_elapsed_time=False,
            ),
            median_automated_stopping_config=google_native.ml.v1.GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs(
                use_elapsed_time=False,
            ),
        ),
        metrics=[google_native.ml.v1.GoogleCloudMlV1_StudyConfig_MetricSpecArgs(
            goal=google_native.ml.v1.GoogleCloudMlV1_StudyConfig_MetricSpecGoal.GOAL_TYPE_UNSPECIFIED,
            metric="string",
        )],
    ),
    study_id="string",
    location="string",
    project="string")

    const examplestudyResourceResourceFromMlv1 = new google_native.ml.v1.Study("examplestudyResourceResourceFromMlv1", {
    studyConfig: {
        parameters: [{
            parameter: "string",
            type: google_native.ml.v1.GoogleCloudMlV1_StudyConfig_ParameterSpecType.ParameterTypeUnspecified,
            categoricalValueSpec: {
                values: ["string"],
            },
            childParameterSpecs: [googleCloudMlV1_StudyConfig_ParameterSpec],
            discreteValueSpec: {
                values: [0],
            },
            doubleValueSpec: {
                maxValue: 0,
                minValue: 0,
            },
            integerValueSpec: {
                maxValue: "string",
                minValue: "string",
            },
            parentCategoricalValues: {
                values: ["string"],
            },
            parentDiscreteValues: {
                values: [0],
            },
            parentIntValues: {
                values: ["string"],
            },
            scaleType: google_native.ml.v1.GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType.ScaleTypeUnspecified,
        }],
        algorithm: google_native.ml.v1.GoogleCloudMlV1__StudyConfigAlgorithm.AlgorithmUnspecified,
        automatedStoppingConfig: {
            decayCurveStoppingConfig: {
                useElapsedTime: false,
            },
            medianAutomatedStoppingConfig: {
                useElapsedTime: false,
            },
        },
        metrics: [{
            goal: google_native.ml.v1.GoogleCloudMlV1_StudyConfig_MetricSpecGoal.GoalTypeUnspecified,
            metric: "string",
        }],
    },
    studyId: "string",
    location: "string",
    project: "string",
});

    type: google-native:ml/v1:Study
properties:
    location: string
    project: string
    studyConfig:
        algorithm: ALGORITHM_UNSPECIFIED
        automatedStoppingConfig:
            decayCurveStoppingConfig:
                useElapsedTime: false
            medianAutomatedStoppingConfig:
                useElapsedTime: false
        metrics:
            - goal: GOAL_TYPE_UNSPECIFIED
              metric: string
        parameters:
            - categoricalValueSpec:
                values:
                    - string
              childParameterSpecs:
                - ${googleCloudMlV1_StudyConfig_ParameterSpec}
              discreteValueSpec:
                values:
                    - 0
              doubleValueSpec:
                maxValue: 0
                minValue: 0
              integerValueSpec:
                maxValue: string
                minValue: string
              parameter: string
              parentCategoricalValues:
                values:
                    - string
              parentDiscreteValues:
                values:
                    - 0
              parentIntValues:
                values:
                    - string
              scaleType: SCALE_TYPE_UNSPECIFIED
              type: PARAMETER_TYPE_UNSPECIFIED
    studyId: string

    Study Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The Study resource accepts the following input properties:

    StudyConfig Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1__StudyConfig
    Configuration of the study.
    StudyId string
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    Location string
    Project string
    StudyConfig GoogleCloudMlV1__StudyConfigArgs
    Configuration of the study.
    StudyId string
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    Location string
    Project string
    studyConfig GoogleCloudMlV1__StudyConfig
    Configuration of the study.
    studyId String
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    location String
    project String
    studyConfig GoogleCloudMlV1__StudyConfig
    Configuration of the study.
    studyId string
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    location string
    project string
    study_config GoogleCloudMlV1StudyConfigArgs
    Configuration of the study.
    study_id str
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    location str
    project str
    studyConfig Property Map
    Configuration of the study.
    studyId String
    Required. The ID to use for the study, which will become the final component of the study's resource name.
    location String
    project String

    Outputs

    All input properties are implicitly available as output properties. Additionally, the Study resource produces the following output properties:

    CreateTime string
    Time at which the study was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    InactiveReason string
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    Name string
    The name of a study.
    State string
    The detailed state of a study.
    CreateTime string
    Time at which the study was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    InactiveReason string
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    Name string
    The name of a study.
    State string
    The detailed state of a study.
    createTime String
    Time at which the study was created.
    id String
    The provider-assigned unique ID for this managed resource.
    inactiveReason String
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    name String
    The name of a study.
    state String
    The detailed state of a study.
    createTime string
    Time at which the study was created.
    id string
    The provider-assigned unique ID for this managed resource.
    inactiveReason string
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    name string
    The name of a study.
    state string
    The detailed state of a study.
    create_time str
    Time at which the study was created.
    id str
    The provider-assigned unique ID for this managed resource.
    inactive_reason str
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    name str
    The name of a study.
    state str
    The detailed state of a study.
    createTime String
    Time at which the study was created.
    id String
    The provider-assigned unique ID for this managed resource.
    inactiveReason String
    A human readable reason why the Study is inactive. This should be empty if a study is ACTIVE or COMPLETED.
    name String
    The name of a study.
    state String
    The detailed state of a study.

    Supporting Types

    GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfig, GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigArgs

    UseElapsedTime bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    UseElapsedTime bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime Boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    use_elapsed_time bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime Boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

    GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponse, GoogleCloudMlV1_AutomatedStoppingConfig_DecayCurveAutomatedStoppingConfigResponseArgs

    UseElapsedTime bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    UseElapsedTime bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime Boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    use_elapsed_time bool
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.
    useElapsedTime Boolean
    If true, measurement.elapsed_time is used as the x-axis of each Trials Decay Curve. Otherwise, Measurement.steps will be used as the x-axis.

    GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfig, GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigArgs

    UseElapsedTime bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    UseElapsedTime bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime Boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    use_elapsed_time bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime Boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

    GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponse, GoogleCloudMlV1_AutomatedStoppingConfig_MedianAutomatedStoppingConfigResponseArgs

    UseElapsedTime bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    UseElapsedTime bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime Boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    use_elapsed_time bool
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.
    useElapsedTime Boolean
    If true, the median automated stopping rule applies to measurement.use_elapsed_time, which means the elapsed_time field of the current trial's latest measurement is used to compute the median objective value for each completed trial.

    GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecArgs

    Values List<string>
    Must be specified if type is CATEGORICAL. The list of possible categories.
    Values []string
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values List<String>
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values string[]
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values Sequence[str]
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values List<String>
    Must be specified if type is CATEGORICAL. The list of possible categories.

    GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponseArgs

    Values List<string>
    Must be specified if type is CATEGORICAL. The list of possible categories.
    Values []string
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values List<String>
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values string[]
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values Sequence[str]
    Must be specified if type is CATEGORICAL. The list of possible categories.
    values List<String>
    Must be specified if type is CATEGORICAL. The list of possible categories.

    GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecArgs

    Values List<double>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    Values []float64
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values List<Double>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values number[]
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values Sequence[float]
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values List<Number>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

    GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponseArgs

    Values List<double>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    Values []float64
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values List<Double>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values number[]
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values Sequence[float]
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.
    values List<Number>
    Must be specified if type is DISCRETE. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values.

    GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecArgs

    MaxValue double
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    MinValue double
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    MaxValue float64
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    MinValue float64
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue Double
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue Double
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue number
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue number
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    max_value float
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    min_value float
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue Number
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue Number
    Must be specified if type is DOUBLE. Minimum value of the parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponseArgs

    MaxValue double
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    MinValue double
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    MaxValue float64
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    MinValue float64
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue Double
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue Double
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue number
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue number
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    max_value float
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    min_value float
    Must be specified if type is DOUBLE. Minimum value of the parameter.
    maxValue Number
    Must be specified if type is DOUBLE. Maximum value of the parameter.
    minValue Number
    Must be specified if type is DOUBLE. Minimum value of the parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecArgs

    MaxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    MinValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    MaxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    MinValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue String
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue String
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    max_value str
    Must be specified if type is INTEGER. Maximum value of the parameter.
    min_value str
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue String
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue String
    Must be specified if type is INTEGER. Minimum value of the parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponseArgs

    MaxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    MinValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    MaxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    MinValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue String
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue String
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue string
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue string
    Must be specified if type is INTEGER. Minimum value of the parameter.
    max_value str
    Must be specified if type is INTEGER. Maximum value of the parameter.
    min_value str
    Must be specified if type is INTEGER. Minimum value of the parameter.
    maxValue String
    Must be specified if type is INTEGER. Maximum value of the parameter.
    minValue String
    Must be specified if type is INTEGER. Minimum value of the parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecArgs

    Values List<string>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    Values []string
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values string[]
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values Sequence[str]
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponseArgs

    Values List<string>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    Values []string
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values string[]
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values Sequence[str]
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'CATEGORICAL'. All values must exist in categorical_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecArgs

    Values List<double>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    Values []float64
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values List<Double>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values number[]
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values Sequence[float]
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values List<Number>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponseArgs

    Values List<double>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    Values []float64
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values List<Double>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values number[]
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values Sequence[float]
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.
    values List<Number>
    Matches values of the parent parameter with type 'DISCRETE'. All values must exist in discrete_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecArgs

    Values List<string>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    Values []string
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values string[]
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values Sequence[str]
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse, GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponseArgs

    Values List<string>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    Values []string
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values string[]
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values Sequence[str]
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.
    values List<String>
    Matches values of the parent parameter with type 'INTEGER'. All values must lie in integer_value_spec of parent parameter.

    GoogleCloudMlV1_StudyConfig_MetricSpec, GoogleCloudMlV1_StudyConfig_MetricSpecArgs

    Goal Pulumi.GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_MetricSpecGoal
    The optimization goal of the metric.
    Metric string
    The name of the metric.
    Goal GoogleCloudMlV1_StudyConfig_MetricSpecGoal
    The optimization goal of the metric.
    Metric string
    The name of the metric.
    goal GoogleCloudMlV1_StudyConfig_MetricSpecGoal
    The optimization goal of the metric.
    metric String
    The name of the metric.
    goal GoogleCloudMlV1_StudyConfig_MetricSpecGoal
    The optimization goal of the metric.
    metric string
    The name of the metric.
    goal GoogleCloudMlV1StudyConfig_MetricSpecGoal
    The optimization goal of the metric.
    metric str
    The name of the metric.
    goal "GOAL_TYPE_UNSPECIFIED" | "MAXIMIZE" | "MINIMIZE"
    The optimization goal of the metric.
    metric String
    The name of the metric.

    GoogleCloudMlV1_StudyConfig_MetricSpecGoal, GoogleCloudMlV1_StudyConfig_MetricSpecGoalArgs

    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GoogleCloudMlV1_StudyConfig_MetricSpecGoalGoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    GoogleCloudMlV1_StudyConfig_MetricSpecGoalMaximize
    MAXIMIZEMaximize the goal metric.
    GoogleCloudMlV1_StudyConfig_MetricSpecGoalMinimize
    MINIMIZEMinimize the goal metric.
    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GoalTypeUnspecified
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    Maximize
    MAXIMIZEMaximize the goal metric.
    Minimize
    MINIMIZEMinimize the goal metric.
    GOAL_TYPE_UNSPECIFIED
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    MAXIMIZE
    MAXIMIZEMaximize the goal metric.
    MINIMIZE
    MINIMIZEMinimize the goal metric.
    "GOAL_TYPE_UNSPECIFIED"
    GOAL_TYPE_UNSPECIFIEDGoal Type will default to maximize.
    "MAXIMIZE"
    MAXIMIZEMaximize the goal metric.
    "MINIMIZE"
    MINIMIZEMinimize the goal metric.

    GoogleCloudMlV1_StudyConfig_MetricSpecResponse, GoogleCloudMlV1_StudyConfig_MetricSpecResponseArgs

    Goal string
    The optimization goal of the metric.
    Metric string
    The name of the metric.
    Goal string
    The optimization goal of the metric.
    Metric string
    The name of the metric.
    goal String
    The optimization goal of the metric.
    metric String
    The name of the metric.
    goal string
    The optimization goal of the metric.
    metric string
    The name of the metric.
    goal str
    The optimization goal of the metric.
    metric str
    The name of the metric.
    goal String
    The optimization goal of the metric.
    metric String
    The name of the metric.

    GoogleCloudMlV1_StudyConfig_ParameterSpec, GoogleCloudMlV1_StudyConfig_ParameterSpecArgs

    Parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    Type Pulumi.GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_ParameterSpecType
    The type of the parameter.
    CategoricalValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec
    The value spec for a 'CATEGORICAL' parameter.
    ChildParameterSpecs List<Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfig_ParameterSpec>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    DiscreteValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec
    The value spec for a 'DISCRETE' parameter.
    DoubleValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec
    The value spec for a 'DOUBLE' parameter.
    IntegerValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec
    The value spec for an 'INTEGER' parameter.
    ParentCategoricalValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec
    ParentDiscreteValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec
    ParentIntValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec
    ScaleType Pulumi.GoogleNative.Ml.V1.GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType
    How the parameter should be scaled. Leave unset for categorical parameters.
    Parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    Type GoogleCloudMlV1_StudyConfig_ParameterSpecType
    The type of the parameter.
    CategoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec
    The value spec for a 'CATEGORICAL' parameter.
    ChildParameterSpecs []GoogleCloudMlV1_StudyConfig_ParameterSpec
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    DiscreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec
    The value spec for a 'DISCRETE' parameter.
    DoubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec
    The value spec for a 'DOUBLE' parameter.
    IntegerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec
    The value spec for an 'INTEGER' parameter.
    ParentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec
    ParentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec
    ParentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec
    ScaleType GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType
    How the parameter should be scaled. Leave unset for categorical parameters.
    parameter String
    The parameter name must be unique amongst all ParameterSpecs.
    type GoogleCloudMlV1_StudyConfig_ParameterSpecType
    The type of the parameter.
    categoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs List<GoogleCloudMlV1_StudyConfig_ParameterSpec>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec
    The value spec for an 'INTEGER' parameter.
    parentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec
    parentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec
    parentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec
    scaleType GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType
    How the parameter should be scaled. Leave unset for categorical parameters.
    parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    type GoogleCloudMlV1_StudyConfig_ParameterSpecType
    The type of the parameter.
    categoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpec
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs GoogleCloudMlV1_StudyConfig_ParameterSpec[]
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpec
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpec
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpec
    The value spec for an 'INTEGER' parameter.
    parentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpec
    parentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpec
    parentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpec
    scaleType GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType
    How the parameter should be scaled. Leave unset for categorical parameters.
    parameter str
    The parameter name must be unique amongst all ParameterSpecs.
    type GoogleCloudMlV1StudyConfig_ParameterSpecType
    The type of the parameter.
    categorical_value_spec GoogleCloudMlV1StudyConfigParameterSpec_CategoricalValueSpec
    The value spec for a 'CATEGORICAL' parameter.
    child_parameter_specs Sequence[GoogleCloudMlV1StudyConfig_ParameterSpec]
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discrete_value_spec GoogleCloudMlV1StudyConfigParameterSpec_DiscreteValueSpec
    The value spec for a 'DISCRETE' parameter.
    double_value_spec GoogleCloudMlV1StudyConfigParameterSpec_DoubleValueSpec
    The value spec for a 'DOUBLE' parameter.
    integer_value_spec GoogleCloudMlV1StudyConfigParameterSpec_IntegerValueSpec
    The value spec for an 'INTEGER' parameter.
    parent_categorical_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentCategoricalValueSpec
    parent_discrete_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentDiscreteValueSpec
    parent_int_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentIntValueSpec
    scale_type GoogleCloudMlV1StudyConfig_ParameterSpecScaleType
    How the parameter should be scaled. Leave unset for categorical parameters.
    parameter String
    The parameter name must be unique amongst all ParameterSpecs.
    type "PARAMETER_TYPE_UNSPECIFIED" | "DOUBLE" | "INTEGER" | "CATEGORICAL" | "DISCRETE"
    The type of the parameter.
    categoricalValueSpec Property Map
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs List<Property Map>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec Property Map
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec Property Map
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec Property Map
    The value spec for an 'INTEGER' parameter.
    parentCategoricalValues Property Map
    parentDiscreteValues Property Map
    parentIntValues Property Map
    scaleType "SCALE_TYPE_UNSPECIFIED" | "UNIT_LINEAR_SCALE" | "UNIT_LOG_SCALE" | "UNIT_REVERSE_LOG_SCALE"
    How the parameter should be scaled. Leave unset for categorical parameters.

    GoogleCloudMlV1_StudyConfig_ParameterSpecResponse, GoogleCloudMlV1_StudyConfig_ParameterSpecResponseArgs

    CategoricalValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse
    The value spec for a 'CATEGORICAL' parameter.
    ChildParameterSpecs List<Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfig_ParameterSpecResponse>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    DiscreteValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse
    The value spec for a 'DISCRETE' parameter.
    DoubleValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse
    The value spec for a 'DOUBLE' parameter.
    IntegerValueSpec Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse
    The value spec for an 'INTEGER' parameter.
    Parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    ParentCategoricalValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse
    ParentDiscreteValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse
    ParentIntValues Pulumi.GoogleNative.Ml.V1.Inputs.GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse
    ScaleType string
    How the parameter should be scaled. Leave unset for categorical parameters.
    Type string
    The type of the parameter.
    CategoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse
    The value spec for a 'CATEGORICAL' parameter.
    ChildParameterSpecs []GoogleCloudMlV1_StudyConfig_ParameterSpecResponse
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    DiscreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse
    The value spec for a 'DISCRETE' parameter.
    DoubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse
    The value spec for a 'DOUBLE' parameter.
    IntegerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse
    The value spec for an 'INTEGER' parameter.
    Parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    ParentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse
    ParentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse
    ParentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse
    ScaleType string
    How the parameter should be scaled. Leave unset for categorical parameters.
    Type string
    The type of the parameter.
    categoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs List<GoogleCloudMlV1_StudyConfig_ParameterSpecResponse>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse
    The value spec for an 'INTEGER' parameter.
    parameter String
    The parameter name must be unique amongst all ParameterSpecs.
    parentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse
    parentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse
    parentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse
    scaleType String
    How the parameter should be scaled. Leave unset for categorical parameters.
    type String
    The type of the parameter.
    categoricalValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_CategoricalValueSpecResponse
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs GoogleCloudMlV1_StudyConfig_ParameterSpecResponse[]
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DiscreteValueSpecResponse
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_DoubleValueSpecResponse
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec GoogleCloudMlV1_StudyConfigParameterSpec_IntegerValueSpecResponse
    The value spec for an 'INTEGER' parameter.
    parameter string
    The parameter name must be unique amongst all ParameterSpecs.
    parentCategoricalValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse
    parentDiscreteValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse
    parentIntValues GoogleCloudMlV1_StudyConfigParameterSpec_MatchingParentIntValueSpecResponse
    scaleType string
    How the parameter should be scaled. Leave unset for categorical parameters.
    type string
    The type of the parameter.
    categorical_value_spec GoogleCloudMlV1StudyConfigParameterSpec_CategoricalValueSpecResponse
    The value spec for a 'CATEGORICAL' parameter.
    child_parameter_specs Sequence[GoogleCloudMlV1StudyConfig_ParameterSpecResponse]
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discrete_value_spec GoogleCloudMlV1StudyConfigParameterSpec_DiscreteValueSpecResponse
    The value spec for a 'DISCRETE' parameter.
    double_value_spec GoogleCloudMlV1StudyConfigParameterSpec_DoubleValueSpecResponse
    The value spec for a 'DOUBLE' parameter.
    integer_value_spec GoogleCloudMlV1StudyConfigParameterSpec_IntegerValueSpecResponse
    The value spec for an 'INTEGER' parameter.
    parameter str
    The parameter name must be unique amongst all ParameterSpecs.
    parent_categorical_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentCategoricalValueSpecResponse
    parent_discrete_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentDiscreteValueSpecResponse
    parent_int_values GoogleCloudMlV1StudyConfigParameterSpec_MatchingParentIntValueSpecResponse
    scale_type str
    How the parameter should be scaled. Leave unset for categorical parameters.
    type str
    The type of the parameter.
    categoricalValueSpec Property Map
    The value spec for a 'CATEGORICAL' parameter.
    childParameterSpecs List<Property Map>
    A child node is active if the parameter's value matches the child node's matching_parent_values. If two items in child_parameter_specs have the same name, they must have disjoint matching_parent_values.
    discreteValueSpec Property Map
    The value spec for a 'DISCRETE' parameter.
    doubleValueSpec Property Map
    The value spec for a 'DOUBLE' parameter.
    integerValueSpec Property Map
    The value spec for an 'INTEGER' parameter.
    parameter String
    The parameter name must be unique amongst all ParameterSpecs.
    parentCategoricalValues Property Map
    parentDiscreteValues Property Map
    parentIntValues Property Map
    scaleType String
    How the parameter should be scaled. Leave unset for categorical parameters.
    type String
    The type of the parameter.

    GoogleCloudMlV1_StudyConfig_ParameterSpecScaleType, GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeArgs

    ScaleTypeUnspecified
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    UnitLinearScale
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    UnitLogScale
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    UnitReverseLogScale
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
    GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeScaleTypeUnspecified
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitLinearScale
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitLogScale
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    GoogleCloudMlV1_StudyConfig_ParameterSpecScaleTypeUnitReverseLogScale
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
    ScaleTypeUnspecified
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    UnitLinearScale
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    UnitLogScale
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    UnitReverseLogScale
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
    ScaleTypeUnspecified
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    UnitLinearScale
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    UnitLogScale
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    UnitReverseLogScale
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
    SCALE_TYPE_UNSPECIFIED
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    UNIT_LINEAR_SCALE
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    UNIT_LOG_SCALE
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    UNIT_REVERSE_LOG_SCALE
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.
    "SCALE_TYPE_UNSPECIFIED"
    SCALE_TYPE_UNSPECIFIEDBy default, no scaling is applied.
    "UNIT_LINEAR_SCALE"
    UNIT_LINEAR_SCALEScales the feasible space to (0, 1) linearly.
    "UNIT_LOG_SCALE"
    UNIT_LOG_SCALEScales the feasible space logarithmically to (0, 1). The entire feasible space must be strictly positive.
    "UNIT_REVERSE_LOG_SCALE"
    UNIT_REVERSE_LOG_SCALEScales the feasible space "reverse" logarithmically to (0, 1). The result is that values close to the top of the feasible space are spread out more than points near the bottom. The entire feasible space must be strictly positive.

    GoogleCloudMlV1_StudyConfig_ParameterSpecType, GoogleCloudMlV1_StudyConfig_ParameterSpecTypeArgs

    ParameterTypeUnspecified
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    Double
    DOUBLEType for real-valued parameters.
    Integer
    INTEGERType for integral parameters.
    Categorical
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    Discrete
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.
    GoogleCloudMlV1_StudyConfig_ParameterSpecTypeParameterTypeUnspecified
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    GoogleCloudMlV1_StudyConfig_ParameterSpecTypeDouble
    DOUBLEType for real-valued parameters.
    GoogleCloudMlV1_StudyConfig_ParameterSpecTypeInteger
    INTEGERType for integral parameters.
    GoogleCloudMlV1_StudyConfig_ParameterSpecTypeCategorical
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    GoogleCloudMlV1_StudyConfig_ParameterSpecTypeDiscrete
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.
    ParameterTypeUnspecified
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    Double
    DOUBLEType for real-valued parameters.
    Integer
    INTEGERType for integral parameters.
    Categorical
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    Discrete
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.
    ParameterTypeUnspecified
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    Double
    DOUBLEType for real-valued parameters.
    Integer
    INTEGERType for integral parameters.
    Categorical
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    Discrete
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.
    PARAMETER_TYPE_UNSPECIFIED
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    DOUBLE
    DOUBLEType for real-valued parameters.
    INTEGER
    INTEGERType for integral parameters.
    CATEGORICAL
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    DISCRETE
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.
    "PARAMETER_TYPE_UNSPECIFIED"
    PARAMETER_TYPE_UNSPECIFIEDYou must specify a valid type. Using this unspecified type will result in an error.
    "DOUBLE"
    DOUBLEType for real-valued parameters.
    "INTEGER"
    INTEGERType for integral parameters.
    "CATEGORICAL"
    CATEGORICALThe parameter is categorical, with a value chosen from the categories field.
    "DISCRETE"
    DISCRETEThe parameter is real valued, with a fixed set of feasible points. If type==DISCRETE, feasible_points must be provided, and {min_value, max_value} will be ignored.

    GoogleCloudMlV1__AutomatedStoppingConfig, GoogleCloudMlV1__AutomatedStoppingConfigArgs

    GoogleCloudMlV1__AutomatedStoppingConfigResponse, GoogleCloudMlV1__AutomatedStoppingConfigResponseArgs

    GoogleCloudMlV1__StudyConfig, GoogleCloudMlV1__StudyConfigArgs

    Parameters []GoogleCloudMlV1_StudyConfig_ParameterSpec
    The set of parameters to tune.
    Algorithm GoogleCloudMlV1__StudyConfigAlgorithm
    The search algorithm specified for the study.
    AutomatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfig
    Configuration for automated stopping of unpromising Trials.
    Metrics []GoogleCloudMlV1_StudyConfig_MetricSpec
    Metric specs for the study.
    parameters List<GoogleCloudMlV1_StudyConfig_ParameterSpec>
    The set of parameters to tune.
    algorithm GoogleCloudMlV1__StudyConfigAlgorithm
    The search algorithm specified for the study.
    automatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfig
    Configuration for automated stopping of unpromising Trials.
    metrics List<GoogleCloudMlV1_StudyConfig_MetricSpec>
    Metric specs for the study.
    parameters GoogleCloudMlV1_StudyConfig_ParameterSpec[]
    The set of parameters to tune.
    algorithm GoogleCloudMlV1__StudyConfigAlgorithm
    The search algorithm specified for the study.
    automatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfig
    Configuration for automated stopping of unpromising Trials.
    metrics GoogleCloudMlV1_StudyConfig_MetricSpec[]
    Metric specs for the study.
    parameters Sequence[GoogleCloudMlV1StudyConfig_ParameterSpec]
    The set of parameters to tune.
    algorithm GoogleCloudMlV1StudyConfigAlgorithm
    The search algorithm specified for the study.
    automated_stopping_config GoogleCloudMlV1AutomatedStoppingConfig
    Configuration for automated stopping of unpromising Trials.
    metrics Sequence[GoogleCloudMlV1StudyConfig_MetricSpec]
    Metric specs for the study.
    parameters List<Property Map>
    The set of parameters to tune.
    algorithm "ALGORITHM_UNSPECIFIED" | "GAUSSIAN_PROCESS_BANDIT" | "GRID_SEARCH" | "RANDOM_SEARCH"
    The search algorithm specified for the study.
    automatedStoppingConfig Property Map
    Configuration for automated stopping of unpromising Trials.
    metrics List<Property Map>
    Metric specs for the study.

    GoogleCloudMlV1__StudyConfigAlgorithm, GoogleCloudMlV1__StudyConfigAlgorithmArgs

    AlgorithmUnspecified
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    GaussianProcessBandit
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    GridSearch
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    RandomSearch
    RANDOM_SEARCHSimple random search within the feasible space.
    GoogleCloudMlV1__StudyConfigAlgorithmAlgorithmUnspecified
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    GoogleCloudMlV1__StudyConfigAlgorithmGaussianProcessBandit
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    GoogleCloudMlV1__StudyConfigAlgorithmGridSearch
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    GoogleCloudMlV1__StudyConfigAlgorithmRandomSearch
    RANDOM_SEARCHSimple random search within the feasible space.
    AlgorithmUnspecified
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    GaussianProcessBandit
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    GridSearch
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    RandomSearch
    RANDOM_SEARCHSimple random search within the feasible space.
    AlgorithmUnspecified
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    GaussianProcessBandit
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    GridSearch
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    RandomSearch
    RANDOM_SEARCHSimple random search within the feasible space.
    ALGORITHM_UNSPECIFIED
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    GAUSSIAN_PROCESS_BANDIT
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    GRID_SEARCH
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    RANDOM_SEARCH
    RANDOM_SEARCHSimple random search within the feasible space.
    "ALGORITHM_UNSPECIFIED"
    ALGORITHM_UNSPECIFIEDThe default algorithm used by the Cloud AI Platform Vizier service.
    "GAUSSIAN_PROCESS_BANDIT"
    GAUSSIAN_PROCESS_BANDITGaussian Process Bandit.
    "GRID_SEARCH"
    GRID_SEARCHSimple grid search within the feasible space. To use grid search, all parameters must be INTEGER, CATEGORICAL, or DISCRETE.
    "RANDOM_SEARCH"
    RANDOM_SEARCHSimple random search within the feasible space.

    GoogleCloudMlV1__StudyConfigResponse, GoogleCloudMlV1__StudyConfigResponseArgs

    Algorithm string
    The search algorithm specified for the study.
    AutomatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfigResponse
    Configuration for automated stopping of unpromising Trials.
    Metrics []GoogleCloudMlV1_StudyConfig_MetricSpecResponse
    Metric specs for the study.
    Parameters []GoogleCloudMlV1_StudyConfig_ParameterSpecResponse
    The set of parameters to tune.
    algorithm String
    The search algorithm specified for the study.
    automatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfigResponse
    Configuration for automated stopping of unpromising Trials.
    metrics List<GoogleCloudMlV1_StudyConfig_MetricSpecResponse>
    Metric specs for the study.
    parameters List<GoogleCloudMlV1_StudyConfig_ParameterSpecResponse>
    The set of parameters to tune.
    algorithm string
    The search algorithm specified for the study.
    automatedStoppingConfig GoogleCloudMlV1__AutomatedStoppingConfigResponse
    Configuration for automated stopping of unpromising Trials.
    metrics GoogleCloudMlV1_StudyConfig_MetricSpecResponse[]
    Metric specs for the study.
    parameters GoogleCloudMlV1_StudyConfig_ParameterSpecResponse[]
    The set of parameters to tune.
    algorithm str
    The search algorithm specified for the study.
    automated_stopping_config GoogleCloudMlV1AutomatedStoppingConfigResponse
    Configuration for automated stopping of unpromising Trials.
    metrics Sequence[GoogleCloudMlV1StudyConfig_MetricSpecResponse]
    Metric specs for the study.
    parameters Sequence[GoogleCloudMlV1StudyConfig_ParameterSpecResponse]
    The set of parameters to tune.
    algorithm String
    The search algorithm specified for the study.
    automatedStoppingConfig Property Map
    Configuration for automated stopping of unpromising Trials.
    metrics List<Property Map>
    Metric specs for the study.
    parameters List<Property Map>
    The set of parameters to tune.

    Package Details

    Repository
    Google Cloud Native pulumi/pulumi-google-native
    License
    Apache-2.0
    google-native logo

    Google Cloud Native is in preview. Google Cloud Classic is fully supported.

    Google Cloud Native v0.32.0 published on Wednesday, Nov 29, 2023 by Pulumi
    pulumi/pulumi-google-native