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AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.103.0 published on Monday, Apr 22, 2024 by Pulumi
pulumi/pulumi-aws-native

aws-native.personalize.Solution

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AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.103.0 published on Monday, Apr 22, 2024 by Pulumi
pulumi/pulumi-aws-native

    Resource schema for AWS::Personalize::Solution.

    Example Usage

    Example

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AwsNative = Pulumi.AwsNative;

return await Deployment.RunAsync(() => 
{
    var mySolution = new AwsNative.Personalize.Solution("mySolution", new()
    {
        Name = "my-solution-name",
        DatasetGroupArn = "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
        RecipeArn = "arn:aws:personalize:::recipe/aws-user-personalization",
        SolutionConfig = new AwsNative.Personalize.Inputs.SolutionConfigArgs
        {
            EventValueThreshold = ".05",
        },
    });

});

    package main

import (
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/personalize"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := personalize.NewSolution(ctx, "mySolution", &personalize.SolutionArgs{
			Name:            pulumi.String("my-solution-name"),
			DatasetGroupArn: pulumi.String("arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name"),
			RecipeArn:       pulumi.String("arn:aws:personalize:::recipe/aws-user-personalization"),
			SolutionConfig: &personalize.SolutionConfigArgs{
				EventValueThreshold: pulumi.String(".05"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    Coming soon!

    import pulumi
import pulumi_aws_native as aws_native

my_solution = aws_native.personalize.Solution("mySolution",
    name="my-solution-name",
    dataset_group_arn="arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
    recipe_arn="arn:aws:personalize:::recipe/aws-user-personalization",
    solution_config=aws_native.personalize.SolutionConfigArgs(
        event_value_threshold=".05",
    ))

    import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const mySolution = new aws_native.personalize.Solution("mySolution", {
    name: "my-solution-name",
    datasetGroupArn: "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
    recipeArn: "arn:aws:personalize:::recipe/aws-user-personalization",
    solutionConfig: {
        eventValueThreshold: ".05",
    },
});

    Coming soon!

    Example

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AwsNative = Pulumi.AwsNative;

return await Deployment.RunAsync(() => 
{
    var mySolution = new AwsNative.Personalize.Solution("mySolution", new()
    {
        Name = "my-solution-name",
        DatasetGroupArn = "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
        RecipeArn = "arn:aws:personalize:::recipe/aws-user-personalization",
        SolutionConfig = new AwsNative.Personalize.Inputs.SolutionConfigArgs
        {
            EventValueThreshold = ".05",
        },
    });

});

    package main

import (
	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/personalize"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := personalize.NewSolution(ctx, "mySolution", &personalize.SolutionArgs{
			Name:            pulumi.String("my-solution-name"),
			DatasetGroupArn: pulumi.String("arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name"),
			RecipeArn:       pulumi.String("arn:aws:personalize:::recipe/aws-user-personalization"),
			SolutionConfig: &personalize.SolutionConfigArgs{
				EventValueThreshold: pulumi.String(".05"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    Coming soon!

    import pulumi
import pulumi_aws_native as aws_native

my_solution = aws_native.personalize.Solution("mySolution",
    name="my-solution-name",
    dataset_group_arn="arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
    recipe_arn="arn:aws:personalize:::recipe/aws-user-personalization",
    solution_config=aws_native.personalize.SolutionConfigArgs(
        event_value_threshold=".05",
    ))

    import * as pulumi from "@pulumi/pulumi";
import * as aws_native from "@pulumi/aws-native";

const mySolution = new aws_native.personalize.Solution("mySolution", {
    name: "my-solution-name",
    datasetGroupArn: "arn:aws:personalize:us-west-2:123456789012:dataset-group/my-dataset-group-name",
    recipeArn: "arn:aws:personalize:::recipe/aws-user-personalization",
    solutionConfig: {
        eventValueThreshold: ".05",
    },
});

    Coming soon!

    Create Solution Resource

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

    Constructor syntax

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

@overload
def Solution(resource_name: str,
             opts: Optional[ResourceOptions] = None,
             dataset_group_arn: Optional[str] = None,
             event_type: Optional[str] = None,
             name: Optional[str] = None,
             perform_auto_ml: Optional[bool] = None,
             perform_hpo: Optional[bool] = None,
             recipe_arn: Optional[str] = None,
             solution_config: Optional[SolutionConfigArgs] = None)
    func NewSolution(ctx *Context, name string, args SolutionArgs, opts ...ResourceOption) (*Solution, error)
    public Solution(string name, SolutionArgs args, CustomResourceOptions? opts = null)
    public Solution(String name, SolutionArgs args)
public Solution(String name, SolutionArgs args, CustomResourceOptions options)

    type: aws-native:personalize:Solution
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 SolutionArgs
    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 SolutionArgs
    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 SolutionArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args SolutionArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args SolutionArgs
    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.

    Coming soon!

    Coming soon!

    Coming soon!

    Coming soon!

    const solutionResource = new aws_native.personalize.Solution("solutionResource", {
    datasetGroupArn: "string",
    eventType: "string",
    name: "string",
    performAutoMl: false,
    performHpo: false,
    recipeArn: "string",
    solutionConfig: {
        algorithmHyperParameters: {
            string: "string",
        },
        autoMlConfig: {
            metricName: "string",
            recipeList: ["string"],
        },
        eventValueThreshold: "string",
        featureTransformationParameters: {
            string: "string",
        },
        hpoConfig: {
            algorithmHyperParameterRanges: {
                categoricalHyperParameterRanges: [{
                    name: "string",
                    values: ["string"],
                }],
                continuousHyperParameterRanges: [{
                    maxValue: 0,
                    minValue: 0,
                    name: "string",
                }],
                integerHyperParameterRanges: [{
                    maxValue: 0,
                    minValue: 0,
                    name: "string",
                }],
            },
            hpoObjective: {
                metricName: "string",
                metricRegex: "string",
                type: aws_native.personalize.SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType.Maximize,
            },
            hpoResourceConfig: {
                maxNumberOfTrainingJobs: "string",
                maxParallelTrainingJobs: "string",
            },
        },
    },
});

    Coming soon!

    Solution 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 Solution resource accepts the following input properties:

    DatasetGroupArn string
    The ARN of the dataset group that provides the training data.
    EventType string
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    Name string
    The name for the solution
    PerformAutoMl bool
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    PerformHpo bool
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    RecipeArn string
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    SolutionConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfig
    DatasetGroupArn string
    The ARN of the dataset group that provides the training data.
    EventType string
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    Name string
    The name for the solution
    PerformAutoMl bool
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    PerformHpo bool
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    RecipeArn string
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    SolutionConfig SolutionConfigArgs
    datasetGroupArn String
    The ARN of the dataset group that provides the training data.
    eventType String
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    name String
    The name for the solution
    performAutoMl Boolean
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    performHpo Boolean
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    recipeArn String
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    solutionConfig SolutionConfig
    datasetGroupArn string
    The ARN of the dataset group that provides the training data.
    eventType string
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    name string
    The name for the solution
    performAutoMl boolean
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    performHpo boolean
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    recipeArn string
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    solutionConfig SolutionConfig
    dataset_group_arn str
    The ARN of the dataset group that provides the training data.
    event_type str
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    name str
    The name for the solution
    perform_auto_ml bool
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    perform_hpo bool
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    recipe_arn str
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    solution_config SolutionConfigArgs
    datasetGroupArn String
    The ARN of the dataset group that provides the training data.
    eventType String
    When your have multiple event types (using an EVENT_TYPE schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model. If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.
    name String
    The name for the solution
    performAutoMl Boolean
    Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
    performHpo Boolean
    Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false. When performing AutoML, this parameter is always true and you should not set it to false.
    recipeArn String
    The ARN of the recipe to use for model training. Only specified when performAutoML is false.
    solutionConfig Property Map

    Outputs

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

    Id string
    The provider-assigned unique ID for this managed resource.
    SolutionArn string
    Id string
    The provider-assigned unique ID for this managed resource.
    SolutionArn string
    id String
    The provider-assigned unique ID for this managed resource.
    solutionArn String
    id string
    The provider-assigned unique ID for this managed resource.
    solutionArn string
    id str
    The provider-assigned unique ID for this managed resource.
    solution_arn str
    id String
    The provider-assigned unique ID for this managed resource.
    solutionArn String

    Supporting Types

    SolutionCategoricalHyperParameterRange, SolutionCategoricalHyperParameterRangeArgs

    Name string
    The name of the hyperparameter.
    Values List<string>
    A list of the categories for the hyperparameter.
    Name string
    The name of the hyperparameter.
    Values []string
    A list of the categories for the hyperparameter.
    name String
    The name of the hyperparameter.
    values List<String>
    A list of the categories for the hyperparameter.
    name string
    The name of the hyperparameter.
    values string[]
    A list of the categories for the hyperparameter.
    name str
    The name of the hyperparameter.
    values Sequence[str]
    A list of the categories for the hyperparameter.
    name String
    The name of the hyperparameter.
    values List<String>
    A list of the categories for the hyperparameter.

    SolutionConfig, SolutionConfigArgs

    AlgorithmHyperParameters Dictionary<string, string>
    Lists the hyperparameter names and ranges.
    AutoMlConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigAutoMlConfigProperties
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    EventValueThreshold string
    Only events with a value greater than or equal to this threshold are used for training a model.
    FeatureTransformationParameters Dictionary<string, string>
    Lists the feature transformation parameters.
    HpoConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigHpoConfigProperties
    Describes the properties for hyperparameter optimization (HPO)
    AlgorithmHyperParameters map[string]string
    Lists the hyperparameter names and ranges.
    AutoMlConfig SolutionConfigAutoMlConfigProperties
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    EventValueThreshold string
    Only events with a value greater than or equal to this threshold are used for training a model.
    FeatureTransformationParameters map[string]string
    Lists the feature transformation parameters.
    HpoConfig SolutionConfigHpoConfigProperties
    Describes the properties for hyperparameter optimization (HPO)
    algorithmHyperParameters Map<String,String>
    Lists the hyperparameter names and ranges.
    autoMlConfig SolutionConfigAutoMlConfigProperties
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    eventValueThreshold String
    Only events with a value greater than or equal to this threshold are used for training a model.
    featureTransformationParameters Map<String,String>
    Lists the feature transformation parameters.
    hpoConfig SolutionConfigHpoConfigProperties
    Describes the properties for hyperparameter optimization (HPO)
    algorithmHyperParameters {[key: string]: string}
    Lists the hyperparameter names and ranges.
    autoMlConfig SolutionConfigAutoMlConfigProperties
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    eventValueThreshold string
    Only events with a value greater than or equal to this threshold are used for training a model.
    featureTransformationParameters {[key: string]: string}
    Lists the feature transformation parameters.
    hpoConfig SolutionConfigHpoConfigProperties
    Describes the properties for hyperparameter optimization (HPO)
    algorithm_hyper_parameters Mapping[str, str]
    Lists the hyperparameter names and ranges.
    auto_ml_config SolutionConfigAutoMlConfigProperties
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    event_value_threshold str
    Only events with a value greater than or equal to this threshold are used for training a model.
    feature_transformation_parameters Mapping[str, str]
    Lists the feature transformation parameters.
    hpo_config SolutionConfigHpoConfigProperties
    Describes the properties for hyperparameter optimization (HPO)
    algorithmHyperParameters Map<String>
    Lists the hyperparameter names and ranges.
    autoMlConfig Property Map
    The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
    eventValueThreshold String
    Only events with a value greater than or equal to this threshold are used for training a model.
    featureTransformationParameters Map<String>
    Lists the feature transformation parameters.
    hpoConfig Property Map
    Describes the properties for hyperparameter optimization (HPO)

    SolutionConfigAutoMlConfigProperties, SolutionConfigAutoMlConfigPropertiesArgs

    MetricName string
    The metric to optimize.
    RecipeList List<string>
    The list of candidate recipes.
    MetricName string
    The metric to optimize.
    RecipeList []string
    The list of candidate recipes.
    metricName String
    The metric to optimize.
    recipeList List<String>
    The list of candidate recipes.
    metricName string
    The metric to optimize.
    recipeList string[]
    The list of candidate recipes.
    metric_name str
    The metric to optimize.
    recipe_list Sequence[str]
    The list of candidate recipes.
    metricName String
    The metric to optimize.
    recipeList List<String>
    The list of candidate recipes.

    SolutionConfigHpoConfigProperties, SolutionConfigHpoConfigPropertiesArgs

    algorithmHyperParameterRanges Property Map
    The hyperparameters and their allowable ranges
    hpoObjective Property Map
    The metric to optimize during HPO.
    hpoResourceConfig Property Map
    Describes the resource configuration for hyperparameter optimization (HPO).

    SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties, SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesPropertiesArgs

    CategoricalHyperParameterRanges []SolutionCategoricalHyperParameterRange
    The categorical hyperparameters and their ranges.
    ContinuousHyperParameterRanges []SolutionContinuousHyperParameterRange
    The continuous hyperparameters and their ranges.
    IntegerHyperParameterRanges []SolutionIntegerHyperParameterRange
    The integer hyperparameters and their ranges.
    categoricalHyperParameterRanges List<SolutionCategoricalHyperParameterRange>
    The categorical hyperparameters and their ranges.
    continuousHyperParameterRanges List<SolutionContinuousHyperParameterRange>
    The continuous hyperparameters and their ranges.
    integerHyperParameterRanges List<SolutionIntegerHyperParameterRange>
    The integer hyperparameters and their ranges.
    categoricalHyperParameterRanges SolutionCategoricalHyperParameterRange[]
    The categorical hyperparameters and their ranges.
    continuousHyperParameterRanges SolutionContinuousHyperParameterRange[]
    The continuous hyperparameters and their ranges.
    integerHyperParameterRanges SolutionIntegerHyperParameterRange[]
    The integer hyperparameters and their ranges.
    categoricalHyperParameterRanges List<Property Map>
    The categorical hyperparameters and their ranges.
    continuousHyperParameterRanges List<Property Map>
    The continuous hyperparameters and their ranges.
    integerHyperParameterRanges List<Property Map>
    The integer hyperparameters and their ranges.

    SolutionConfigHpoConfigPropertiesHpoObjectiveProperties, SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesArgs

    MetricName string
    The name of the metric
    MetricRegex string
    A regular expression for finding the metric in the training job logs.
    Type Pulumi.AwsNative.Personalize.SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType
    The type of the metric. Valid values are Maximize and Minimize.
    MetricName string
    The name of the metric
    MetricRegex string
    A regular expression for finding the metric in the training job logs.
    Type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType
    The type of the metric. Valid values are Maximize and Minimize.
    metricName String
    The name of the metric
    metricRegex String
    A regular expression for finding the metric in the training job logs.
    type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType
    The type of the metric. Valid values are Maximize and Minimize.
    metricName string
    The name of the metric
    metricRegex string
    A regular expression for finding the metric in the training job logs.
    type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType
    The type of the metric. Valid values are Maximize and Minimize.
    metric_name str
    The name of the metric
    metric_regex str
    A regular expression for finding the metric in the training job logs.
    type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType
    The type of the metric. Valid values are Maximize and Minimize.
    metricName String
    The name of the metric
    metricRegex String
    A regular expression for finding the metric in the training job logs.
    type "Maximize" | "Minimize"
    The type of the metric. Valid values are Maximize and Minimize.

    SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType, SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeArgs

    Maximize
    Maximize
    Minimize
    Minimize
    SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeMaximize
    Maximize
    SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeMinimize
    Minimize
    Maximize
    Maximize
    Minimize
    Minimize
    Maximize
    Maximize
    Minimize
    Minimize
    MAXIMIZE
    Maximize
    MINIMIZE
    Minimize
    "Maximize"
    Maximize
    "Minimize"
    Minimize

    SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties, SolutionConfigHpoConfigPropertiesHpoResourceConfigPropertiesArgs

    MaxNumberOfTrainingJobs string
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    MaxParallelTrainingJobs string
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
    MaxNumberOfTrainingJobs string
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    MaxParallelTrainingJobs string
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
    maxNumberOfTrainingJobs String
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    maxParallelTrainingJobs String
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
    maxNumberOfTrainingJobs string
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    maxParallelTrainingJobs string
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
    max_number_of_training_jobs str
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    max_parallel_training_jobs str
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
    maxNumberOfTrainingJobs String
    The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
    maxParallelTrainingJobs String
    The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

    SolutionContinuousHyperParameterRange, SolutionContinuousHyperParameterRangeArgs

    MaxValue double
    The maximum allowable value for the hyperparameter.
    MinValue double
    The minimum allowable value for the hyperparameter.
    Name string
    The name of the hyperparameter.
    MaxValue float64
    The maximum allowable value for the hyperparameter.
    MinValue float64
    The minimum allowable value for the hyperparameter.
    Name string
    The name of the hyperparameter.
    maxValue Double
    The maximum allowable value for the hyperparameter.
    minValue Double
    The minimum allowable value for the hyperparameter.
    name String
    The name of the hyperparameter.
    maxValue number
    The maximum allowable value for the hyperparameter.
    minValue number
    The minimum allowable value for the hyperparameter.
    name string
    The name of the hyperparameter.
    max_value float
    The maximum allowable value for the hyperparameter.
    min_value float
    The minimum allowable value for the hyperparameter.
    name str
    The name of the hyperparameter.
    maxValue Number
    The maximum allowable value for the hyperparameter.
    minValue Number
    The minimum allowable value for the hyperparameter.
    name String
    The name of the hyperparameter.

    SolutionIntegerHyperParameterRange, SolutionIntegerHyperParameterRangeArgs

    MaxValue int
    The maximum allowable value for the hyperparameter.
    MinValue int
    The minimum allowable value for the hyperparameter.
    Name string
    The name of the hyperparameter.
    MaxValue int
    The maximum allowable value for the hyperparameter.
    MinValue int
    The minimum allowable value for the hyperparameter.
    Name string
    The name of the hyperparameter.
    maxValue Integer
    The maximum allowable value for the hyperparameter.
    minValue Integer
    The minimum allowable value for the hyperparameter.
    name String
    The name of the hyperparameter.
    maxValue number
    The maximum allowable value for the hyperparameter.
    minValue number
    The minimum allowable value for the hyperparameter.
    name string
    The name of the hyperparameter.
    max_value int
    The maximum allowable value for the hyperparameter.
    min_value int
    The minimum allowable value for the hyperparameter.
    name str
    The name of the hyperparameter.
    maxValue Number
    The maximum allowable value for the hyperparameter.
    minValue Number
    The minimum allowable value for the hyperparameter.
    name String
    The name of the hyperparameter.

    Package Details

    Repository
    AWS Native pulumi/pulumi-aws-native
    License
    Apache-2.0
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    AWS Native is in preview. AWS Classic is fully supported.

    AWS Native v0.103.0 published on Monday, Apr 22, 2024 by Pulumi
    pulumi/pulumi-aws-native