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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.
@file:Suppress("NAME_SHADOWING", "DEPRECATION")
package com.pulumi.azurenative.machinelearningservices.kotlin
import com.pulumi.azurenative.machinelearningservices.kotlin.outputs.SystemDataResponse
import com.pulumi.azurenative.machinelearningservices.kotlin.outputs.SystemDataResponse.Companion.toKotlin
import com.pulumi.core.Output
import com.pulumi.kotlin.KotlinCustomResource
import com.pulumi.kotlin.PulumiTagMarker
import com.pulumi.kotlin.ResourceMapper
import com.pulumi.kotlin.options.CustomResourceOptions
import com.pulumi.kotlin.options.CustomResourceOptionsBuilder
import com.pulumi.resources.Resource
import kotlin.Any
import kotlin.Boolean
import kotlin.String
import kotlin.Suppress
import kotlin.Unit
/**
* Builder for [Job].
*/
@PulumiTagMarker
public class JobResourceBuilder internal constructor() {
public var name: String? = null
public var args: JobArgs = JobArgs()
public var opts: CustomResourceOptions = CustomResourceOptions()
/**
* @param name The _unique_ name of the resulting resource.
*/
public fun name(`value`: String) {
this.name = value
}
/**
* @param block The arguments to use to populate this resource's properties.
*/
public suspend fun args(block: suspend JobArgsBuilder.() -> Unit) {
val builder = JobArgsBuilder()
block(builder)
this.args = builder.build()
}
/**
* @param block A bag of options that control this resource's behavior.
*/
public suspend fun opts(block: suspend CustomResourceOptionsBuilder.() -> Unit) {
this.opts = com.pulumi.kotlin.options.CustomResourceOptions.opts(block)
}
internal fun build(): Job {
val builtJavaResource =
com.pulumi.azurenative.machinelearningservices.Job(
this.name,
this.args.toJava(),
this.opts.toJava(),
)
return Job(builtJavaResource)
}
}
/**
* Azure Resource Manager resource envelope.
* Azure REST API version: 2023-04-01. Prior API version in Azure Native 1.x: 2021-03-01-preview.
* Other available API versions: 2021-03-01-preview, 2022-02-01-preview, 2023-04-01-preview, 2023-06-01-preview, 2023-08-01-preview, 2023-10-01, 2024-01-01-preview, 2024-04-01, 2024-04-01-preview, 2024-07-01-preview.
* ## Example Usage
* ### CreateOrUpdate AutoML Job.
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using AzureNative = Pulumi.AzureNative;
* return await Deployment.RunAsync(() =>
* {
* var job = new AzureNative.MachineLearningServices.Job("job", new()
* {
* Id = "string",
* JobBaseProperties = new AzureNative.MachineLearningServices.Inputs.AutoMLJobArgs
* {
* ComputeId = "string",
* Description = "string",
* DisplayName = "string",
* EnvironmentId = "string",
* EnvironmentVariables =
* {
* { "string", "string" },
* },
* ExperimentName = "string",
* Identity = new AzureNative.MachineLearningServices.Inputs.AmlTokenArgs
* {
* IdentityType = "AMLToken",
* },
* IsArchived = false,
* JobType = "AutoML",
* Outputs =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.UriFileJobOutputArgs
* {
* Description = "string",
* JobOutputType = "uri_file",
* Mode = AzureNative.MachineLearningServices.OutputDeliveryMode.ReadWriteMount,
* Uri = "string",
* } },
* },
* Properties =
* {
* { "string", "string" },
* },
* Resources = new AzureNative.MachineLearningServices.Inputs.JobResourceConfigurationArgs
* {
* InstanceCount = 1,
* InstanceType = "string",
* Properties =
* {
* { "string", new Dictionary
* {
* ["9bec0ab0-c62f-4fa9-a97c-7b24bbcc90ad"] = null,
* } },
* },
* },
* Services =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.JobServiceArgs
* {
* Endpoint = "string",
* JobServiceType = "string",
* Port = 1,
* Properties =
* {
* { "string", "string" },
* },
* } },
* },
* Tags =
* {
* { "string", "string" },
* },
* TaskDetails = new AzureNative.MachineLearningServices.Inputs.ImageClassificationArgs
* {
* LimitSettings = new AzureNative.MachineLearningServices.Inputs.ImageLimitSettingsArgs
* {
* MaxTrials = 2,
* },
* ModelSettings = new AzureNative.MachineLearningServices.Inputs.ImageModelSettingsClassificationArgs
* {
* ValidationCropSize = 2,
* },
* SearchSpace = new[]
* {
* new AzureNative.MachineLearningServices.Inputs.ImageModelDistributionSettingsClassificationArgs
* {
* ValidationCropSize = "choice(2, 360)",
* },
* },
* TargetColumnName = "string",
* TaskType = "ImageClassification",
* TrainingData = new AzureNative.MachineLearningServices.Inputs.MLTableJobInputArgs
* {
* JobInputType = "mltable",
* Uri = "string",
* },
* },
* },
* ResourceGroupName = "test-rg",
* WorkspaceName = "my-aml-workspace",
* });
* });
* ```
* ```go
* package main
* import (
* machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := machinelearningservices.NewJob(ctx, "job", &machinelearningservices.JobArgs{
* Id: pulumi.String("string"),
* JobBaseProperties: &machinelearningservices.AutoMLJobArgs{
* ComputeId: pulumi.String("string"),
* Description: pulumi.String("string"),
* DisplayName: pulumi.String("string"),
* EnvironmentId: pulumi.String("string"),
* EnvironmentVariables: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* ExperimentName: pulumi.String("string"),
* Identity: machinelearningservices.AmlToken{
* IdentityType: "AMLToken",
* },
* IsArchived: pulumi.Bool(false),
* JobType: pulumi.String("AutoML"),
* Outputs: pulumi.Map{
* "string": machinelearningservices.UriFileJobOutput{
* Description: "string",
* JobOutputType: "uri_file",
* Mode: machinelearningservices.OutputDeliveryModeReadWriteMount,
* Uri: "string",
* },
* },
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* Resources: &machinelearningservices.JobResourceConfigurationArgs{
* InstanceCount: pulumi.Int(1),
* InstanceType: pulumi.String("string"),
* Properties: pulumi.Map{
* "string": pulumi.Any(map[string]interface{}{
* "9bec0ab0-c62f-4fa9-a97c-7b24bbcc90ad": nil,
* }),
* },
* },
* Services: machinelearningservices.JobServiceMap{
* "string": &machinelearningservices.JobServiceArgs{
* Endpoint: pulumi.String("string"),
* JobServiceType: pulumi.String("string"),
* Port: pulumi.Int(1),
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* },
* Tags: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* TaskDetails: machinelearningservices.ImageClassification{
* LimitSettings: machinelearningservices.ImageLimitSettings{
* MaxTrials: 2,
* },
* ModelSettings: machinelearningservices.ImageModelSettingsClassification{
* ValidationCropSize: 2,
* },
* SearchSpace: []machinelearningservices.ImageModelDistributionSettingsClassification{
* {
* ValidationCropSize: "choice(2, 360)",
* },
* },
* TargetColumnName: "string",
* TaskType: "ImageClassification",
* TrainingData: machinelearningservices.MLTableJobInput{
* JobInputType: "mltable",
* Uri: "string",
* },
* },
* },
* ResourceGroupName: pulumi.String("test-rg"),
* WorkspaceName: pulumi.String("my-aml-workspace"),
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.azurenative.machinelearningservices.Job;
* import com.pulumi.azurenative.machinelearningservices.JobArgs;
* import java.util.List;
* import java.util.ArrayList;
* import java.util.Map;
* import java.io.File;
* import java.nio.file.Files;
* import java.nio.file.Paths;
* public class App {
* public static void main(String[] args) {
* Pulumi.run(App::stack);
* }
* public static void stack(Context ctx) {
* var job = new Job("job", JobArgs.builder()
* .id("string")
* .jobBaseProperties(AutoMLJobArgs.builder()
* .computeId("string")
* .description("string")
* .displayName("string")
* .environmentId("string")
* .environmentVariables(Map.of("string", "string"))
* .experimentName("string")
* .identity(AmlTokenArgs.builder()
* .identityType("AMLToken")
* .build())
* .isArchived(false)
* .jobType("AutoML")
* .outputs(Map.of("string", Map.ofEntries(
* Map.entry("description", "string"),
* Map.entry("jobOutputType", "uri_file"),
* Map.entry("mode", "ReadWriteMount"),
* Map.entry("uri", "string")
* )))
* .properties(Map.of("string", "string"))
* .resources(JobResourceConfigurationArgs.builder()
* .instanceCount(1)
* .instanceType("string")
* .properties(Map.of("string", Map.of("9bec0ab0-c62f-4fa9-a97c-7b24bbcc90ad", null)))
* .build())
* .services(Map.of("string", Map.ofEntries(
* Map.entry("endpoint", "string"),
* Map.entry("jobServiceType", "string"),
* Map.entry("port", 1),
* Map.entry("properties", Map.of("string", "string"))
* )))
* .tags(Map.of("string", "string"))
* .taskDetails(ImageClassificationArgs.builder()
* .limitSettings(ImageLimitSettingsArgs.builder()
* .maxTrials(2)
* .build())
* .modelSettings(ImageModelSettingsClassificationArgs.builder()
* .validationCropSize(2)
* .build())
* .searchSpace(ImageModelDistributionSettingsClassificationArgs.builder()
* .validationCropSize("choice(2, 360)")
* .build())
* .targetColumnName("string")
* .taskType("ImageClassification")
* .trainingData(MLTableJobInputArgs.builder()
* .jobInputType("mltable")
* .uri("string")
* .build())
* .build())
* .build())
* .resourceGroupName("test-rg")
* .workspaceName("my-aml-workspace")
* .build());
* }
* }
* ```
* ### CreateOrUpdate Command Job.
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using AzureNative = Pulumi.AzureNative;
* return await Deployment.RunAsync(() =>
* {
* var job = new AzureNative.MachineLearningServices.Job("job", new()
* {
* Id = "string",
* JobBaseProperties = new AzureNative.MachineLearningServices.Inputs.CommandJobArgs
* {
* CodeId = "string",
* Command = "string",
* ComputeId = "string",
* Description = "string",
* DisplayName = "string",
* Distribution = new AzureNative.MachineLearningServices.Inputs.TensorFlowArgs
* {
* DistributionType = "TensorFlow",
* ParameterServerCount = 1,
* WorkerCount = 1,
* },
* EnvironmentId = "string",
* EnvironmentVariables =
* {
* { "string", "string" },
* },
* ExperimentName = "string",
* Identity = new AzureNative.MachineLearningServices.Inputs.AmlTokenArgs
* {
* IdentityType = "AMLToken",
* },
* Inputs =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.LiteralJobInputArgs
* {
* Description = "string",
* JobInputType = "literal",
* Value = "string",
* } },
* },
* JobType = "Command",
* Limits = new AzureNative.MachineLearningServices.Inputs.CommandJobLimitsArgs
* {
* JobLimitsType = "Command",
* Timeout = "PT5M",
* },
* Outputs =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.UriFileJobOutputArgs
* {
* Description = "string",
* JobOutputType = "uri_file",
* Mode = AzureNative.MachineLearningServices.OutputDeliveryMode.ReadWriteMount,
* Uri = "string",
* } },
* },
* Properties =
* {
* { "string", "string" },
* },
* Resources = new AzureNative.MachineLearningServices.Inputs.JobResourceConfigurationArgs
* {
* InstanceCount = 1,
* InstanceType = "string",
* Properties =
* {
* { "string", new Dictionary
* {
* ["e6b6493e-7d5e-4db3-be1e-306ec641327e"] = null,
* } },
* },
* },
* Services =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.JobServiceArgs
* {
* Endpoint = "string",
* JobServiceType = "string",
* Port = 1,
* Properties =
* {
* { "string", "string" },
* },
* } },
* },
* Tags =
* {
* { "string", "string" },
* },
* },
* ResourceGroupName = "test-rg",
* WorkspaceName = "my-aml-workspace",
* });
* });
* ```
* ```go
* package main
* import (
* machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := machinelearningservices.NewJob(ctx, "job", &machinelearningservices.JobArgs{
* Id: pulumi.String("string"),
* JobBaseProperties: &machinelearningservices.CommandJobArgs{
* CodeId: pulumi.String("string"),
* Command: pulumi.String("string"),
* ComputeId: pulumi.String("string"),
* Description: pulumi.String("string"),
* DisplayName: pulumi.String("string"),
* Distribution: machinelearningservices.TensorFlow{
* DistributionType: "TensorFlow",
* ParameterServerCount: 1,
* WorkerCount: 1,
* },
* EnvironmentId: pulumi.String("string"),
* EnvironmentVariables: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* ExperimentName: pulumi.String("string"),
* Identity: machinelearningservices.AmlToken{
* IdentityType: "AMLToken",
* },
* Inputs: pulumi.Map{
* "string": machinelearningservices.LiteralJobInput{
* Description: "string",
* JobInputType: "literal",
* Value: "string",
* },
* },
* JobType: pulumi.String("Command"),
* Limits: &machinelearningservices.CommandJobLimitsArgs{
* JobLimitsType: pulumi.String("Command"),
* Timeout: pulumi.String("PT5M"),
* },
* Outputs: pulumi.Map{
* "string": machinelearningservices.UriFileJobOutput{
* Description: "string",
* JobOutputType: "uri_file",
* Mode: machinelearningservices.OutputDeliveryModeReadWriteMount,
* Uri: "string",
* },
* },
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* Resources: &machinelearningservices.JobResourceConfigurationArgs{
* InstanceCount: pulumi.Int(1),
* InstanceType: pulumi.String("string"),
* Properties: pulumi.Map{
* "string": pulumi.Any(map[string]interface{}{
* "e6b6493e-7d5e-4db3-be1e-306ec641327e": nil,
* }),
* },
* },
* Services: machinelearningservices.JobServiceMap{
* "string": &machinelearningservices.JobServiceArgs{
* Endpoint: pulumi.String("string"),
* JobServiceType: pulumi.String("string"),
* Port: pulumi.Int(1),
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* },
* Tags: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* ResourceGroupName: pulumi.String("test-rg"),
* WorkspaceName: pulumi.String("my-aml-workspace"),
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.azurenative.machinelearningservices.Job;
* import com.pulumi.azurenative.machinelearningservices.JobArgs;
* import java.util.List;
* import java.util.ArrayList;
* import java.util.Map;
* import java.io.File;
* import java.nio.file.Files;
* import java.nio.file.Paths;
* public class App {
* public static void main(String[] args) {
* Pulumi.run(App::stack);
* }
* public static void stack(Context ctx) {
* var job = new Job("job", JobArgs.builder()
* .id("string")
* .jobBaseProperties(CommandJobArgs.builder()
* .codeId("string")
* .command("string")
* .computeId("string")
* .description("string")
* .displayName("string")
* .distribution(TensorFlowArgs.builder()
* .distributionType("TensorFlow")
* .parameterServerCount(1)
* .workerCount(1)
* .build())
* .environmentId("string")
* .environmentVariables(Map.of("string", "string"))
* .experimentName("string")
* .identity(AmlTokenArgs.builder()
* .identityType("AMLToken")
* .build())
* .inputs(Map.of("string", Map.ofEntries(
* Map.entry("description", "string"),
* Map.entry("jobInputType", "literal"),
* Map.entry("value", "string")
* )))
* .jobType("Command")
* .limits(CommandJobLimitsArgs.builder()
* .jobLimitsType("Command")
* .timeout("PT5M")
* .build())
* .outputs(Map.of("string", Map.ofEntries(
* Map.entry("description", "string"),
* Map.entry("jobOutputType", "uri_file"),
* Map.entry("mode", "ReadWriteMount"),
* Map.entry("uri", "string")
* )))
* .properties(Map.of("string", "string"))
* .resources(JobResourceConfigurationArgs.builder()
* .instanceCount(1)
* .instanceType("string")
* .properties(Map.of("string", Map.of("e6b6493e-7d5e-4db3-be1e-306ec641327e", null)))
* .build())
* .services(Map.of("string", Map.ofEntries(
* Map.entry("endpoint", "string"),
* Map.entry("jobServiceType", "string"),
* Map.entry("port", 1),
* Map.entry("properties", Map.of("string", "string"))
* )))
* .tags(Map.of("string", "string"))
* .build())
* .resourceGroupName("test-rg")
* .workspaceName("my-aml-workspace")
* .build());
* }
* }
* ```
* ### CreateOrUpdate Pipeline Job.
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using AzureNative = Pulumi.AzureNative;
* return await Deployment.RunAsync(() =>
* {
* var job = new AzureNative.MachineLearningServices.Job("job", new()
* {
* Id = "string",
* JobBaseProperties = new AzureNative.MachineLearningServices.Inputs.PipelineJobArgs
* {
* ComputeId = "string",
* Description = "string",
* DisplayName = "string",
* ExperimentName = "string",
* Inputs =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.LiteralJobInputArgs
* {
* Description = "string",
* JobInputType = "literal",
* Value = "string",
* } },
* },
* JobType = "Pipeline",
* Outputs =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.UriFileJobOutputArgs
* {
* Description = "string",
* JobOutputType = "uri_file",
* Mode = AzureNative.MachineLearningServices.OutputDeliveryMode.Upload,
* Uri = "string",
* } },
* },
* Properties =
* {
* { "string", "string" },
* },
* Services =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.JobServiceArgs
* {
* Endpoint = "string",
* JobServiceType = "string",
* Port = 1,
* Properties =
* {
* { "string", "string" },
* },
* } },
* },
* Settings = null,
* Tags =
* {
* { "string", "string" },
* },
* },
* ResourceGroupName = "test-rg",
* WorkspaceName = "my-aml-workspace",
* });
* });
* ```
* ```go
* package main
* import (
* machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := machinelearningservices.NewJob(ctx, "job", &machinelearningservices.JobArgs{
* Id: pulumi.String("string"),
* JobBaseProperties: &machinelearningservices.PipelineJobArgs{
* ComputeId: pulumi.String("string"),
* Description: pulumi.String("string"),
* DisplayName: pulumi.String("string"),
* ExperimentName: pulumi.String("string"),
* Inputs: pulumi.Map{
* "string": machinelearningservices.LiteralJobInput{
* Description: "string",
* JobInputType: "literal",
* Value: "string",
* },
* },
* JobType: pulumi.String("Pipeline"),
* Outputs: pulumi.Map{
* "string": machinelearningservices.UriFileJobOutput{
* Description: "string",
* JobOutputType: "uri_file",
* Mode: machinelearningservices.OutputDeliveryModeUpload,
* Uri: "string",
* },
* },
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* Services: machinelearningservices.JobServiceMap{
* "string": &machinelearningservices.JobServiceArgs{
* Endpoint: pulumi.String("string"),
* JobServiceType: pulumi.String("string"),
* Port: pulumi.Int(1),
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* },
* Settings: pulumi.Any(nil),
* Tags: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* ResourceGroupName: pulumi.String("test-rg"),
* WorkspaceName: pulumi.String("my-aml-workspace"),
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.azurenative.machinelearningservices.Job;
* import com.pulumi.azurenative.machinelearningservices.JobArgs;
* import java.util.List;
* import java.util.ArrayList;
* import java.util.Map;
* import java.io.File;
* import java.nio.file.Files;
* import java.nio.file.Paths;
* public class App {
* public static void main(String[] args) {
* Pulumi.run(App::stack);
* }
* public static void stack(Context ctx) {
* var job = new Job("job", JobArgs.builder()
* .id("string")
* .jobBaseProperties(PipelineJobArgs.builder()
* .computeId("string")
* .description("string")
* .displayName("string")
* .experimentName("string")
* .inputs(Map.of("string", Map.ofEntries(
* Map.entry("description", "string"),
* Map.entry("jobInputType", "literal"),
* Map.entry("value", "string")
* )))
* .jobType("Pipeline")
* .outputs(Map.of("string", Map.ofEntries(
* Map.entry("description", "string"),
* Map.entry("jobOutputType", "uri_file"),
* Map.entry("mode", "Upload"),
* Map.entry("uri", "string")
* )))
* .properties(Map.of("string", "string"))
* .services(Map.of("string", Map.ofEntries(
* Map.entry("endpoint", "string"),
* Map.entry("jobServiceType", "string"),
* Map.entry("port", 1),
* Map.entry("properties", Map.of("string", "string"))
* )))
* .settings()
* .tags(Map.of("string", "string"))
* .build())
* .resourceGroupName("test-rg")
* .workspaceName("my-aml-workspace")
* .build());
* }
* }
* ```
* ### CreateOrUpdate Sweep Job.
* ```csharp
* using System.Collections.Generic;
* using System.Linq;
* using Pulumi;
* using AzureNative = Pulumi.AzureNative;
* return await Deployment.RunAsync(() =>
* {
* var job = new AzureNative.MachineLearningServices.Job("job", new()
* {
* Id = "string",
* JobBaseProperties = new AzureNative.MachineLearningServices.Inputs.SweepJobArgs
* {
* ComputeId = "string",
* Description = "string",
* DisplayName = "string",
* EarlyTermination = new AzureNative.MachineLearningServices.Inputs.MedianStoppingPolicyArgs
* {
* DelayEvaluation = 1,
* EvaluationInterval = 1,
* PolicyType = "MedianStopping",
* },
* ExperimentName = "string",
* JobType = "Sweep",
* Limits = new AzureNative.MachineLearningServices.Inputs.SweepJobLimitsArgs
* {
* JobLimitsType = "Sweep",
* MaxConcurrentTrials = 1,
* MaxTotalTrials = 1,
* TrialTimeout = "PT1S",
* },
* Objective = new AzureNative.MachineLearningServices.Inputs.ObjectiveArgs
* {
* Goal = AzureNative.MachineLearningServices.Goal.Minimize,
* PrimaryMetric = "string",
* },
* Properties =
* {
* { "string", "string" },
* },
* SamplingAlgorithm = new AzureNative.MachineLearningServices.Inputs.GridSamplingAlgorithmArgs
* {
* SamplingAlgorithmType = "Grid",
* },
* SearchSpace = new Dictionary
* {
* ["string"] = new Dictionary
* {
* },
* },
* Services =
* {
* { "string", new AzureNative.MachineLearningServices.Inputs.JobServiceArgs
* {
* Endpoint = "string",
* JobServiceType = "string",
* Port = 1,
* Properties =
* {
* { "string", "string" },
* },
* } },
* },
* Tags =
* {
* { "string", "string" },
* },
* Trial = new AzureNative.MachineLearningServices.Inputs.TrialComponentArgs
* {
* CodeId = "string",
* Command = "string",
* Distribution = new AzureNative.MachineLearningServices.Inputs.MpiArgs
* {
* DistributionType = "Mpi",
* ProcessCountPerInstance = 1,
* },
* EnvironmentId = "string",
* EnvironmentVariables =
* {
* { "string", "string" },
* },
* Resources = new AzureNative.MachineLearningServices.Inputs.JobResourceConfigurationArgs
* {
* InstanceCount = 1,
* InstanceType = "string",
* Properties =
* {
* { "string", new Dictionary
* {
* ["e6b6493e-7d5e-4db3-be1e-306ec641327e"] = null,
* } },
* },
* },
* },
* },
* ResourceGroupName = "test-rg",
* WorkspaceName = "my-aml-workspace",
* });
* });
* ```
* ```go
* package main
* import (
* machinelearningservices "github.com/pulumi/pulumi-azure-native-sdk/machinelearningservices/v2"
* "github.com/pulumi/pulumi/sdk/v3/go/pulumi"
* )
* func main() {
* pulumi.Run(func(ctx *pulumi.Context) error {
* _, err := machinelearningservices.NewJob(ctx, "job", &machinelearningservices.JobArgs{
* Id: pulumi.String("string"),
* JobBaseProperties: &machinelearningservices.SweepJobArgs{
* ComputeId: pulumi.String("string"),
* Description: pulumi.String("string"),
* DisplayName: pulumi.String("string"),
* EarlyTermination: machinelearningservices.MedianStoppingPolicy{
* DelayEvaluation: 1,
* EvaluationInterval: 1,
* PolicyType: "MedianStopping",
* },
* ExperimentName: pulumi.String("string"),
* JobType: pulumi.String("Sweep"),
* Limits: &machinelearningservices.SweepJobLimitsArgs{
* JobLimitsType: pulumi.String("Sweep"),
* MaxConcurrentTrials: pulumi.Int(1),
* MaxTotalTrials: pulumi.Int(1),
* TrialTimeout: pulumi.String("PT1S"),
* },
* Objective: &machinelearningservices.ObjectiveArgs{
* Goal: pulumi.String(machinelearningservices.GoalMinimize),
* PrimaryMetric: pulumi.String("string"),
* },
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* SamplingAlgorithm: machinelearningservices.GridSamplingAlgorithm{
* SamplingAlgorithmType: "Grid",
* },
* SearchSpace: pulumi.Any(map[string]interface{}{
* "string": nil,
* }),
* Services: machinelearningservices.JobServiceMap{
* "string": &machinelearningservices.JobServiceArgs{
* Endpoint: pulumi.String("string"),
* JobServiceType: pulumi.String("string"),
* Port: pulumi.Int(1),
* Properties: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* },
* },
* Tags: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* Trial: &machinelearningservices.TrialComponentArgs{
* CodeId: pulumi.String("string"),
* Command: pulumi.String("string"),
* Distribution: machinelearningservices.Mpi{
* DistributionType: "Mpi",
* ProcessCountPerInstance: 1,
* },
* EnvironmentId: pulumi.String("string"),
* EnvironmentVariables: pulumi.StringMap{
* "string": pulumi.String("string"),
* },
* Resources: &machinelearningservices.JobResourceConfigurationArgs{
* InstanceCount: pulumi.Int(1),
* InstanceType: pulumi.String("string"),
* Properties: pulumi.Map{
* "string": pulumi.Any(map[string]interface{}{
* "e6b6493e-7d5e-4db3-be1e-306ec641327e": nil,
* }),
* },
* },
* },
* },
* ResourceGroupName: pulumi.String("test-rg"),
* WorkspaceName: pulumi.String("my-aml-workspace"),
* })
* if err != nil {
* return err
* }
* return nil
* })
* }
* ```
* ```java
* package generated_program;
* import com.pulumi.Context;
* import com.pulumi.Pulumi;
* import com.pulumi.core.Output;
* import com.pulumi.azurenative.machinelearningservices.Job;
* import com.pulumi.azurenative.machinelearningservices.JobArgs;
* import java.util.List;
* import java.util.ArrayList;
* import java.util.Map;
* import java.io.File;
* import java.nio.file.Files;
* import java.nio.file.Paths;
* public class App {
* public static void main(String[] args) {
* Pulumi.run(App::stack);
* }
* public static void stack(Context ctx) {
* var job = new Job("job", JobArgs.builder()
* .id("string")
* .jobBaseProperties(SweepJobArgs.builder()
* .computeId("string")
* .description("string")
* .displayName("string")
* .earlyTermination(MedianStoppingPolicyArgs.builder()
* .delayEvaluation(1)
* .evaluationInterval(1)
* .policyType("MedianStopping")
* .build())
* .experimentName("string")
* .jobType("Sweep")
* .limits(SweepJobLimitsArgs.builder()
* .jobLimitsType("Sweep")
* .maxConcurrentTrials(1)
* .maxTotalTrials(1)
* .trialTimeout("PT1S")
* .build())
* .objective(ObjectiveArgs.builder()
* .goal("Minimize")
* .primaryMetric("string")
* .build())
* .properties(Map.of("string", "string"))
* .samplingAlgorithm(GridSamplingAlgorithmArgs.builder()
* .samplingAlgorithmType("Grid")
* .build())
* .searchSpace(Map.of("string", ))
* .services(Map.of("string", Map.ofEntries(
* Map.entry("endpoint", "string"),
* Map.entry("jobServiceType", "string"),
* Map.entry("port", 1),
* Map.entry("properties", Map.of("string", "string"))
* )))
* .tags(Map.of("string", "string"))
* .trial(TrialComponentArgs.builder()
* .codeId("string")
* .command("string")
* .distribution(MpiArgs.builder()
* .distributionType("Mpi")
* .processCountPerInstance(1)
* .build())
* .environmentId("string")
* .environmentVariables(Map.of("string", "string"))
* .resources(JobResourceConfigurationArgs.builder()
* .instanceCount(1)
* .instanceType("string")
* .properties(Map.of("string", Map.of("e6b6493e-7d5e-4db3-be1e-306ec641327e", null)))
* .build())
* .build())
* .build())
* .resourceGroupName("test-rg")
* .workspaceName("my-aml-workspace")
* .build());
* }
* }
* ```
* ## Import
* An existing resource can be imported using its type token, name, and identifier, e.g.
* ```sh
* $ pulumi import azure-native:machinelearningservices:Job string /subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.MachineLearningServices/workspaces/{workspaceName}/jobs/{id}
* ```
*/
public class Job internal constructor(
override val javaResource: com.pulumi.azurenative.machinelearningservices.Job,
) : KotlinCustomResource(javaResource, JobMapper) {
/**
* [Required] Additional attributes of the entity.
*/
public val jobBaseProperties: Output
get() = javaResource.jobBaseProperties().applyValue({ args0 -> args0 })
/**
* The name of the resource
*/
public val name: Output
get() = javaResource.name().applyValue({ args0 -> args0 })
/**
* Azure Resource Manager metadata containing createdBy and modifiedBy information.
*/
public val systemData: Output
get() = javaResource.systemData().applyValue({ args0 -> args0.let({ args0 -> toKotlin(args0) }) })
/**
* The type of the resource. E.g. "Microsoft.Compute/virtualMachines" or "Microsoft.Storage/storageAccounts"
*/
public val type: Output
get() = javaResource.type().applyValue({ args0 -> args0 })
}
public object JobMapper : ResourceMapper {
override fun supportsMappingOfType(javaResource: Resource): Boolean =
com.pulumi.azurenative.machinelearningservices.Job::class == javaResource::class
override fun map(javaResource: Resource): Job = Job(
javaResource as
com.pulumi.azurenative.machinelearningservices.Job,
)
}
/**
* @see [Job].
* @param name The _unique_ name of the resulting resource.
* @param block Builder for [Job].
*/
public suspend fun job(name: String, block: suspend JobResourceBuilder.() -> Unit): Job {
val builder = JobResourceBuilder()
builder.name(name)
block(builder)
return builder.build()
}
/**
* @see [Job].
* @param name The _unique_ name of the resulting resource.
*/
public fun job(name: String): Job {
val builder = JobResourceBuilder()
builder.name(name)
return builder.build()
}
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