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The AWS SDK for Kotlin client for Personalize
// Code generated by smithy-kotlin-codegen. DO NOT EDIT!
package aws.sdk.kotlin.services.personalize.model
import aws.smithy.kotlin.runtime.SdkDsl
/**
* Describes the configuration properties for the solution.
*/
public class SolutionConfig private constructor(builder: Builder) {
/**
* Lists the algorithm hyperparameters and their values.
*/
public val algorithmHyperParameters: Map? = builder.algorithmHyperParameters
/**
* The [AutoMLConfig](https://docs.aws.amazon.com/personalize/latest/dg/API_AutoMLConfig.html) object containing a list of recipes to search when AutoML is performed.
*/
public val autoMlConfig: aws.sdk.kotlin.services.personalize.model.AutoMlConfig? = builder.autoMlConfig
/**
* Specifies the automatic training configuration to use.
*/
public val autoTrainingConfig: aws.sdk.kotlin.services.personalize.model.AutoTrainingConfig? = builder.autoTrainingConfig
/**
* Only events with a value greater than or equal to this threshold are used for training a model.
*/
public val eventValueThreshold: kotlin.String? = builder.eventValueThreshold
/**
* Lists the feature transformation parameters.
*/
public val featureTransformationParameters: Map? = builder.featureTransformationParameters
/**
* Describes the properties for hyperparameter optimization (HPO).
*/
public val hpoConfig: aws.sdk.kotlin.services.personalize.model.HpoConfig? = builder.hpoConfig
/**
* Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see [Optimizing a solution](https://docs.aws.amazon.com/personalize/latest/dg/optimizing-solution-for-objective.html).
*/
public val optimizationObjective: aws.sdk.kotlin.services.personalize.model.OptimizationObjective? = builder.optimizationObjective
/**
* Specifies the training data configuration to use when creating a custom solution version (trained model).
*/
public val trainingDataConfig: aws.sdk.kotlin.services.personalize.model.TrainingDataConfig? = builder.trainingDataConfig
public companion object {
public operator fun invoke(block: Builder.() -> kotlin.Unit): aws.sdk.kotlin.services.personalize.model.SolutionConfig = Builder().apply(block).build()
}
override fun toString(): kotlin.String = buildString {
append("SolutionConfig(")
append("algorithmHyperParameters=$algorithmHyperParameters,")
append("autoMlConfig=$autoMlConfig,")
append("autoTrainingConfig=$autoTrainingConfig,")
append("eventValueThreshold=$eventValueThreshold,")
append("featureTransformationParameters=$featureTransformationParameters,")
append("hpoConfig=$hpoConfig,")
append("optimizationObjective=$optimizationObjective,")
append("trainingDataConfig=$trainingDataConfig")
append(")")
}
override fun hashCode(): kotlin.Int {
var result = algorithmHyperParameters?.hashCode() ?: 0
result = 31 * result + (autoMlConfig?.hashCode() ?: 0)
result = 31 * result + (autoTrainingConfig?.hashCode() ?: 0)
result = 31 * result + (eventValueThreshold?.hashCode() ?: 0)
result = 31 * result + (featureTransformationParameters?.hashCode() ?: 0)
result = 31 * result + (hpoConfig?.hashCode() ?: 0)
result = 31 * result + (optimizationObjective?.hashCode() ?: 0)
result = 31 * result + (trainingDataConfig?.hashCode() ?: 0)
return result
}
override fun equals(other: kotlin.Any?): kotlin.Boolean {
if (this === other) return true
if (other == null || this::class != other::class) return false
other as SolutionConfig
if (algorithmHyperParameters != other.algorithmHyperParameters) return false
if (autoMlConfig != other.autoMlConfig) return false
if (autoTrainingConfig != other.autoTrainingConfig) return false
if (eventValueThreshold != other.eventValueThreshold) return false
if (featureTransformationParameters != other.featureTransformationParameters) return false
if (hpoConfig != other.hpoConfig) return false
if (optimizationObjective != other.optimizationObjective) return false
if (trainingDataConfig != other.trainingDataConfig) return false
return true
}
public inline fun copy(block: Builder.() -> kotlin.Unit = {}): aws.sdk.kotlin.services.personalize.model.SolutionConfig = Builder(this).apply(block).build()
@SdkDsl
public class Builder {
/**
* Lists the algorithm hyperparameters and their values.
*/
public var algorithmHyperParameters: Map? = null
/**
* The [AutoMLConfig](https://docs.aws.amazon.com/personalize/latest/dg/API_AutoMLConfig.html) object containing a list of recipes to search when AutoML is performed.
*/
public var autoMlConfig: aws.sdk.kotlin.services.personalize.model.AutoMlConfig? = null
/**
* Specifies the automatic training configuration to use.
*/
public var autoTrainingConfig: aws.sdk.kotlin.services.personalize.model.AutoTrainingConfig? = null
/**
* Only events with a value greater than or equal to this threshold are used for training a model.
*/
public var eventValueThreshold: kotlin.String? = null
/**
* Lists the feature transformation parameters.
*/
public var featureTransformationParameters: Map? = null
/**
* Describes the properties for hyperparameter optimization (HPO).
*/
public var hpoConfig: aws.sdk.kotlin.services.personalize.model.HpoConfig? = null
/**
* Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see [Optimizing a solution](https://docs.aws.amazon.com/personalize/latest/dg/optimizing-solution-for-objective.html).
*/
public var optimizationObjective: aws.sdk.kotlin.services.personalize.model.OptimizationObjective? = null
/**
* Specifies the training data configuration to use when creating a custom solution version (trained model).
*/
public var trainingDataConfig: aws.sdk.kotlin.services.personalize.model.TrainingDataConfig? = null
@PublishedApi
internal constructor()
@PublishedApi
internal constructor(x: aws.sdk.kotlin.services.personalize.model.SolutionConfig) : this() {
this.algorithmHyperParameters = x.algorithmHyperParameters
this.autoMlConfig = x.autoMlConfig
this.autoTrainingConfig = x.autoTrainingConfig
this.eventValueThreshold = x.eventValueThreshold
this.featureTransformationParameters = x.featureTransformationParameters
this.hpoConfig = x.hpoConfig
this.optimizationObjective = x.optimizationObjective
this.trainingDataConfig = x.trainingDataConfig
}
@PublishedApi
internal fun build(): aws.sdk.kotlin.services.personalize.model.SolutionConfig = SolutionConfig(this)
/**
* construct an [aws.sdk.kotlin.services.personalize.model.AutoMlConfig] inside the given [block]
*/
public fun autoMlConfig(block: aws.sdk.kotlin.services.personalize.model.AutoMlConfig.Builder.() -> kotlin.Unit) {
this.autoMlConfig = aws.sdk.kotlin.services.personalize.model.AutoMlConfig.invoke(block)
}
/**
* construct an [aws.sdk.kotlin.services.personalize.model.AutoTrainingConfig] inside the given [block]
*/
public fun autoTrainingConfig(block: aws.sdk.kotlin.services.personalize.model.AutoTrainingConfig.Builder.() -> kotlin.Unit) {
this.autoTrainingConfig = aws.sdk.kotlin.services.personalize.model.AutoTrainingConfig.invoke(block)
}
/**
* construct an [aws.sdk.kotlin.services.personalize.model.HpoConfig] inside the given [block]
*/
public fun hpoConfig(block: aws.sdk.kotlin.services.personalize.model.HpoConfig.Builder.() -> kotlin.Unit) {
this.hpoConfig = aws.sdk.kotlin.services.personalize.model.HpoConfig.invoke(block)
}
/**
* construct an [aws.sdk.kotlin.services.personalize.model.OptimizationObjective] inside the given [block]
*/
public fun optimizationObjective(block: aws.sdk.kotlin.services.personalize.model.OptimizationObjective.Builder.() -> kotlin.Unit) {
this.optimizationObjective = aws.sdk.kotlin.services.personalize.model.OptimizationObjective.invoke(block)
}
/**
* construct an [aws.sdk.kotlin.services.personalize.model.TrainingDataConfig] inside the given [block]
*/
public fun trainingDataConfig(block: aws.sdk.kotlin.services.personalize.model.TrainingDataConfig.Builder.() -> kotlin.Unit) {
this.trainingDataConfig = aws.sdk.kotlin.services.personalize.model.TrainingDataConfig.invoke(block)
}
internal fun correctErrors(): Builder {
return this
}
}
}