com.pulumi.gcp.vertex.kotlin.outputs.AiEndpointDeployedModelDedicatedResourceMachineSpec.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.outputs

import kotlin.Int
import kotlin.String
import kotlin.Suppress

/**
 *
 * @property acceleratorCount (Output)
 * The number of accelerators to attach to the machine.
 * @property acceleratorType (Output)
 * 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 (Output)
 * 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 this field is optional, and the default value is `n1-standard-2`. For BatchPredictionJob or as part of WorkerPoolSpec this field is required. TODO(rsurowka): Try to better unify the required vs optional.
 */
public data class AiEndpointDeployedModelDedicatedResourceMachineSpec(
    public val acceleratorCount: Int? = null,
    public val acceleratorType: String? = null,
    public val machineType: String? = null,
) {
    public companion object {
        public fun toKotlin(javaType: com.pulumi.gcp.vertex.outputs.AiEndpointDeployedModelDedicatedResourceMachineSpec): AiEndpointDeployedModelDedicatedResourceMachineSpec =
            AiEndpointDeployedModelDedicatedResourceMachineSpec(
                acceleratorCount = javaType.acceleratorCount().map({ args0 -> args0 }).orElse(null),
                acceleratorType = javaType.acceleratorType().map({ args0 -> args0 }).orElse(null),
                machineType = javaType.machineType().map({ args0 -> args0 }).orElse(null),
            )
    }
}