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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
public class CreateSolutionRequest private constructor(builder: Builder) {
/**
* The Amazon Resource Name (ARN) of the dataset group that provides the training data.
*/
public val datasetGroupArn: kotlin.String? = builder.datasetGroupArn
/**
* 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.
*/
public val eventType: kotlin.String? = builder.eventType
/**
* The name for the solution.
*/
public val name: kotlin.String? = builder.name
/**
* We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see [Choosing a recipe](https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html).
*
* Whether to perform automated machine learning (AutoML). The default is `false`. For this case, you must specify `recipeArn`.
*
* When set to `true`, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit `recipeArn`. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.
*/
public val performAutoMl: kotlin.Boolean? = builder.performAutoMl
/**
* Whether the solution uses automatic training to create new solution versions (trained models). The default is `True` and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a `schedulingExpression` in the `AutoTrainingConfig` as part of solution configuration. For more information about automatic training, see [Configuring automatic training](https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html).
*
* Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.
*
* After training starts, you can get the solution version's Amazon Resource Name (ARN) with the [ListSolutionVersions](https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html) API operation. To get its status, use the [DescribeSolutionVersion](https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html).
*/
public val performAutoTraining: kotlin.Boolean? = builder.performAutoTraining
/**
* 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`.
*/
public val performHpo: kotlin.Boolean? = builder.performHpo
/**
* The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when `performAutoML` is false. For information about different Amazon Personalize recipes and their ARNs, see [Choosing a recipe](https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html).
*/
public val recipeArn: kotlin.String? = builder.recipeArn
/**
* The configuration to use with the solution. When `performAutoML` is set to true, Amazon Personalize only evaluates the `autoMLConfig` section of the solution configuration.
*
* Amazon Personalize doesn't support configuring the `hpoObjective` at this time.
*/
public val solutionConfig: aws.sdk.kotlin.services.personalize.model.SolutionConfig? = builder.solutionConfig
/**
* A list of [tags](https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html) to apply to the solution.
*/
public val tags: List? = builder.tags
public companion object {
public operator fun invoke(block: Builder.() -> kotlin.Unit): aws.sdk.kotlin.services.personalize.model.CreateSolutionRequest = Builder().apply(block).build()
}
override fun toString(): kotlin.String = buildString {
append("CreateSolutionRequest(")
append("datasetGroupArn=$datasetGroupArn,")
append("eventType=$eventType,")
append("name=$name,")
append("performAutoMl=$performAutoMl,")
append("performAutoTraining=$performAutoTraining,")
append("performHpo=$performHpo,")
append("recipeArn=$recipeArn,")
append("solutionConfig=$solutionConfig,")
append("tags=$tags")
append(")")
}
override fun hashCode(): kotlin.Int {
var result = datasetGroupArn?.hashCode() ?: 0
result = 31 * result + (eventType?.hashCode() ?: 0)
result = 31 * result + (name?.hashCode() ?: 0)
result = 31 * result + (performAutoMl?.hashCode() ?: 0)
result = 31 * result + (performAutoTraining?.hashCode() ?: 0)
result = 31 * result + (performHpo?.hashCode() ?: 0)
result = 31 * result + (recipeArn?.hashCode() ?: 0)
result = 31 * result + (solutionConfig?.hashCode() ?: 0)
result = 31 * result + (tags?.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 CreateSolutionRequest
if (datasetGroupArn != other.datasetGroupArn) return false
if (eventType != other.eventType) return false
if (name != other.name) return false
if (performAutoMl != other.performAutoMl) return false
if (performAutoTraining != other.performAutoTraining) return false
if (performHpo != other.performHpo) return false
if (recipeArn != other.recipeArn) return false
if (solutionConfig != other.solutionConfig) return false
if (tags != other.tags) return false
return true
}
public inline fun copy(block: Builder.() -> kotlin.Unit = {}): aws.sdk.kotlin.services.personalize.model.CreateSolutionRequest = Builder(this).apply(block).build()
@SdkDsl
public class Builder {
/**
* The Amazon Resource Name (ARN) of the dataset group that provides the training data.
*/
public var datasetGroupArn: kotlin.String? = null
/**
* 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.
*/
public var eventType: kotlin.String? = null
/**
* The name for the solution.
*/
public var name: kotlin.String? = null
/**
* We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see [Choosing a recipe](https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html).
*
* Whether to perform automated machine learning (AutoML). The default is `false`. For this case, you must specify `recipeArn`.
*
* When set to `true`, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit `recipeArn`. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.
*/
public var performAutoMl: kotlin.Boolean? = null
/**
* Whether the solution uses automatic training to create new solution versions (trained models). The default is `True` and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a `schedulingExpression` in the `AutoTrainingConfig` as part of solution configuration. For more information about automatic training, see [Configuring automatic training](https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html).
*
* Automatic solution version creation starts one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.
*
* After training starts, you can get the solution version's Amazon Resource Name (ARN) with the [ListSolutionVersions](https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html) API operation. To get its status, use the [DescribeSolutionVersion](https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html).
*/
public var performAutoTraining: kotlin.Boolean? = null
/**
* 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`.
*/
public var performHpo: kotlin.Boolean? = null
/**
* The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when `performAutoML` is false. For information about different Amazon Personalize recipes and their ARNs, see [Choosing a recipe](https://docs.aws.amazon.com/personalize/latest/dg/working-with-predefined-recipes.html).
*/
public var recipeArn: kotlin.String? = null
/**
* The configuration to use with the solution. When `performAutoML` is set to true, Amazon Personalize only evaluates the `autoMLConfig` section of the solution configuration.
*
* Amazon Personalize doesn't support configuring the `hpoObjective` at this time.
*/
public var solutionConfig: aws.sdk.kotlin.services.personalize.model.SolutionConfig? = null
/**
* A list of [tags](https://docs.aws.amazon.com/personalize/latest/dg/tagging-resources.html) to apply to the solution.
*/
public var tags: List? = null
@PublishedApi
internal constructor()
@PublishedApi
internal constructor(x: aws.sdk.kotlin.services.personalize.model.CreateSolutionRequest) : this() {
this.datasetGroupArn = x.datasetGroupArn
this.eventType = x.eventType
this.name = x.name
this.performAutoMl = x.performAutoMl
this.performAutoTraining = x.performAutoTraining
this.performHpo = x.performHpo
this.recipeArn = x.recipeArn
this.solutionConfig = x.solutionConfig
this.tags = x.tags
}
@PublishedApi
internal fun build(): aws.sdk.kotlin.services.personalize.model.CreateSolutionRequest = CreateSolutionRequest(this)
/**
* construct an [aws.sdk.kotlin.services.personalize.model.SolutionConfig] inside the given [block]
*/
public fun solutionConfig(block: aws.sdk.kotlin.services.personalize.model.SolutionConfig.Builder.() -> kotlin.Unit) {
this.solutionConfig = aws.sdk.kotlin.services.personalize.model.SolutionConfig.invoke(block)
}
internal fun correctErrors(): Builder {
return this
}
}
}