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

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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.AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs.builder
import com.pulumi.kotlin.ConvertibleToJava
import com.pulumi.kotlin.PulumiTagMarker
import kotlin.String
import kotlin.Suppress
import kotlin.jvm.JvmName

/**
 *
 * @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)
 * See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).
 * For [DeployedModel](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints#DeployedModel) this field is optional, and the default value is n1-standard-2. For [BatchPredictionJob](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs#BatchPredictionJob) or as part of [WorkerPoolSpec](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/CustomJobSpec#WorkerPoolSpec) this field is required.
 */
public data class AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs(
    public val machineType: Output? = null,
) :
    ConvertibleToJava {
    override fun toJava(): com.pulumi.gcp.vertex.inputs.AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs =
        com.pulumi.gcp.vertex.inputs.AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs.builder()
            .machineType(machineType?.applyValue({ args0 -> args0 })).build()
}

/**
 * Builder for [AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs].
 */
@PulumiTagMarker
public class AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgsBuilder internal constructor() {
    private var machineType: Output? = null

    /**
     * @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)
     * See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).
     * For [DeployedModel](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints#DeployedModel) this field is optional, and the default value is n1-standard-2. For [BatchPredictionJob](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs#BatchPredictionJob) or as part of [WorkerPoolSpec](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/CustomJobSpec#WorkerPoolSpec) this field is required.
     */
    @JvmName("spnnksfhsykinbem")
    public suspend fun machineType(`value`: Output) {
        this.machineType = 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)
     * See the [list of machine types supported for custom training](https://cloud.google.com/vertex-ai/docs/training/configure-compute#machine-types).
     * For [DeployedModel](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints#DeployedModel) this field is optional, and the default value is n1-standard-2. For [BatchPredictionJob](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.batchPredictionJobs#BatchPredictionJob) or as part of [WorkerPoolSpec](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/CustomJobSpec#WorkerPoolSpec) this field is required.
     */
    @JvmName("gbhnwxquhyprctjc")
    public suspend fun machineType(`value`: String?) {
        val toBeMapped = value
        val mapped = toBeMapped?.let({ args0 -> of(args0) })
        this.machineType = mapped
    }

    internal fun build(): AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs =
        AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpecArgs(
            machineType = machineType,
        )
}