com.pulumi.gcp.vertex.kotlin.inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs.kt Maven / Gradle / Ivy

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Build cloud applications and infrastructure by combining the safety and reliability of infrastructure as code with the power of the Kotlin programming language.
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@file:Suppress("NAME_SHADOWING", "DEPRECATION")

package com.pulumi.gcp.vertex.kotlin.inputs

import com.pulumi.core.Output
import com.pulumi.core.Output.of
import com.pulumi.gcp.vertex.inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs.builder
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import kotlin.Int
import kotlin.String
import kotlin.Suppress
import kotlin.jvm.JvmName

/**
 *
 * @property acceleratorCount The number of accelerators to attach to the machine.
 * @property acceleratorType The type of accelerator(s) that may be attached to the machine as per accelerator_count. See possible values [here](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/MachineSpec#AcceleratorType).
 * @property machineType The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types).
 */
public data class AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs(
    public val acceleratorCount: Output? = null,
    public val acceleratorType: Output? = null,
    public val machineType: Output? = null,
) :
    ConvertibleToJava {
    override fun toJava(): com.pulumi.gcp.vertex.inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs =
        com.pulumi.gcp.vertex.inputs.AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs.builder()
            .acceleratorCount(acceleratorCount?.applyValue({ args0 -> args0 }))
            .acceleratorType(acceleratorType?.applyValue({ args0 -> args0 }))
            .machineType(machineType?.applyValue({ args0 -> args0 })).build()
}

/**
 * Builder for [AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs].
 */
@PulumiTagMarker
public class AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgsBuilder internal constructor() {
    private var acceleratorCount: Output? = null

    private var acceleratorType: Output? = null

    private var machineType: Output? = null

    /**
     * @param value The number of accelerators to attach to the machine.
     */
    @JvmName("doppqoebmmuiwpcc")
    public suspend fun acceleratorCount(`value`: Output) {
        this.acceleratorCount = value
    }

    /**
     * @param value The type of accelerator(s) that may be attached to the machine as per accelerator_count. See possible values [here](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/MachineSpec#AcceleratorType).
     */
    @JvmName("ynetxxwblfavjctx")
    public suspend fun acceleratorType(`value`: Output) {
        this.acceleratorType = value
    }

    /**
     * @param value The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types).
     */
    @JvmName("oeicsjudhfvibtsa")
    public suspend fun machineType(`value`: Output) {
        this.machineType = value
    }

    /**
     * @param value The number of accelerators to attach to the machine.
     */
    @JvmName("ntldvsgcvfdpgywt")
    public suspend fun acceleratorCount(`value`: Int?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.acceleratorCount = mapped
    }

    /**
     * @param value The type of accelerator(s) that may be attached to the machine as per accelerator_count. See possible values [here](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/MachineSpec#AcceleratorType).
     */
    @JvmName("acstqxchopkbceen")
    public suspend fun acceleratorType(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.acceleratorType = mapped
    }

    /**
     * @param value The type of the machine. See the [list of machine types supported for prediction](https://cloud.google.com/vertex-ai/docs/predictions/configure-compute#machine-types).
     */
    @JvmName("bcssoaftihahvtdl")
    public suspend fun machineType(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.machineType = mapped
    }

    internal fun build(): AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs =
        AiDeploymentResourcePoolDedicatedResourcesMachineSpecArgs(
            acceleratorCount = acceleratorCount,
            acceleratorType = acceleratorType,
            machineType = machineType,
        )
}