com.pulumi.gcp.vertex.kotlin.outputs.AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpec.kt Maven / Gradle / Ivy

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

package com.pulumi.gcp.vertex.kotlin.outputs

import kotlin.String
import kotlin.Suppress

/**
 *
 * @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 AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpec(
    public val machineType: String? = null,
) {
    public companion object {
        public fun toKotlin(javaType: com.pulumi.gcp.vertex.outputs.AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpec): AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpec =
            AiIndexEndpointDeployedIndexDedicatedResourcesMachineSpec(
                machineType = javaType.machineType().map({ args0 -> args0 }).orElse(null),
            )
    }
}