com.pulumi.awsnative.personalize.kotlin.inputs.SolutionConfigArgs.kt Maven / Gradle / Ivy

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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.awsnative.personalize.kotlin.inputs

import com.pulumi.awsnative.personalize.inputs.SolutionConfigArgs.builder
import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.applySuspend
import kotlin.Pair
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
import kotlin.collections.Map
import kotlin.jvm.JvmName

/**
 * The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration.
 * @property algorithmHyperParameters Lists the hyperparameter names and ranges.
 * @property autoMlConfig The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
 * @property eventValueThreshold Only events with a value greater than or equal to this threshold are used for training a model.
 * @property featureTransformationParameters Lists the feature transformation parameters.
 * @property hpoConfig Describes the properties for hyperparameter optimization (HPO)
 */
public data class SolutionConfigArgs(
    public val algorithmHyperParameters: Output>? = null,
    public val autoMlConfig: Output? = null,
    public val eventValueThreshold: Output? = null,
    public val featureTransformationParameters: Output>? = null,
    public val hpoConfig: Output? = null,
) : ConvertibleToJava {
    override fun toJava(): com.pulumi.awsnative.personalize.inputs.SolutionConfigArgs =
        com.pulumi.awsnative.personalize.inputs.SolutionConfigArgs.builder()
            .algorithmHyperParameters(
                algorithmHyperParameters?.applyValue({ args0 ->
                    args0.map({ args0 ->
                        args0.key.to(args0.value)
                    }).toMap()
                }),
            )
            .autoMlConfig(autoMlConfig?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) }))
            .eventValueThreshold(eventValueThreshold?.applyValue({ args0 -> args0 }))
            .featureTransformationParameters(
                featureTransformationParameters?.applyValue({ args0 ->
                    args0.map({ args0 -> args0.key.to(args0.value) }).toMap()
                }),
            )
            .hpoConfig(hpoConfig?.applyValue({ args0 -> args0.let({ args0 -> args0.toJava() }) })).build()
}

/**
 * Builder for [SolutionConfigArgs].
 */
@PulumiTagMarker
public class SolutionConfigArgsBuilder internal constructor() {
    private var algorithmHyperParameters: Output>? = null

    private var autoMlConfig: Output? = null

    private var eventValueThreshold: Output? = null

    private var featureTransformationParameters: Output>? = null

    private var hpoConfig: Output? = null

    /**
     * @param value Lists the hyperparameter names and ranges.
     */
    @JvmName("uwaylqjdhqodxlla")
    public suspend fun algorithmHyperParameters(`value`: Output>) {
        this.algorithmHyperParameters = value
    }

    /**
     * @param value The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
     */
    @JvmName("dbtdijrleyfyqaxt")
    public suspend fun autoMlConfig(`value`: Output) {
        this.autoMlConfig = value
    }

    /**
     * @param value Only events with a value greater than or equal to this threshold are used for training a model.
     */
    @JvmName("fibbwogruriaxttb")
    public suspend fun eventValueThreshold(`value`: Output) {
        this.eventValueThreshold = value
    }

    /**
     * @param value Lists the feature transformation parameters.
     */
    @JvmName("upsdthorhfecmlec")
    public suspend fun featureTransformationParameters(`value`: Output>) {
        this.featureTransformationParameters = value
    }

    /**
     * @param value Describes the properties for hyperparameter optimization (HPO)
     */
    @JvmName("gcjgjogbvbocguwa")
    public suspend fun hpoConfig(`value`: Output) {
        this.hpoConfig = value
    }

    /**
     * @param value Lists the hyperparameter names and ranges.
     */
    @JvmName("wqbyfchbpxvervuq")
    public suspend fun algorithmHyperParameters(`value`: Map?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.algorithmHyperParameters = mapped
    }

    /**
     * @param values Lists the hyperparameter names and ranges.
     */
    @JvmName("nnxgdopvogpkfaxg")
    public fun algorithmHyperParameters(vararg values: Pair) {
        val toBeMapped = values.toMap()
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.algorithmHyperParameters = mapped
    }

    /**
     * @param value The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
     */
    @JvmName("comqedrfhahtokqt")
    public suspend fun autoMlConfig(`value`: SolutionConfigAutoMlConfigPropertiesArgs?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.autoMlConfig = mapped
    }

    /**
     * @param argument The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
     */
    @JvmName("sufjqlbrkarfobuw")
    public suspend fun autoMlConfig(argument: suspend SolutionConfigAutoMlConfigPropertiesArgsBuilder.() -> Unit) {
        val toBeMapped = SolutionConfigAutoMlConfigPropertiesArgsBuilder().applySuspend {
            argument()
        }.build()
        val mapped = of(toBeMapped)
        this.autoMlConfig = mapped
    }

    /**
     * @param value Only events with a value greater than or equal to this threshold are used for training a model.
     */
    @JvmName("vhitaeqcoapbofio")
    public suspend fun eventValueThreshold(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.eventValueThreshold = mapped
    }

    /**
     * @param value Lists the feature transformation parameters.
     */
    @JvmName("ejudssljeyswmnji")
    public suspend fun featureTransformationParameters(`value`: Map?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.featureTransformationParameters = mapped
    }

    /**
     * @param values Lists the feature transformation parameters.
     */
    @JvmName("paartjqsxjqohocn")
    public fun featureTransformationParameters(vararg values: Pair) {
        val toBeMapped = values.toMap()
        val mapped = toBeMapped.let({ args0 -> of(args0) })
        this.featureTransformationParameters = mapped
    }

    /**
     * @param value Describes the properties for hyperparameter optimization (HPO)
     */
    @JvmName("tkapvgcueynwitlg")
    public suspend fun hpoConfig(`value`: SolutionConfigHpoConfigPropertiesArgs?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.hpoConfig = mapped
    }

    /**
     * @param argument Describes the properties for hyperparameter optimization (HPO)
     */
    @JvmName("tbqjtlkghgevidqs")
    public suspend fun hpoConfig(argument: suspend SolutionConfigHpoConfigPropertiesArgsBuilder.() -> Unit) {
        val toBeMapped = SolutionConfigHpoConfigPropertiesArgsBuilder().applySuspend {
            argument()
        }.build()
        val mapped = of(toBeMapped)
        this.hpoConfig = mapped
    }

    internal fun build(): SolutionConfigArgs = SolutionConfigArgs(
        algorithmHyperParameters = algorithmHyperParameters,
        autoMlConfig = autoMlConfig,
        eventValueThreshold = eventValueThreshold,
        featureTransformationParameters = featureTransformationParameters,
        hpoConfig = hpoConfig,
    )
}