Labeling
data class LabelingJobArgs(val labelingJobId: Output<String>? = null, val properties: Output<LabelingJobPropertiesArgs>? = null, val resourceGroupName: Output<String>? = null, val workspaceName: Output<String>? = null) : ConvertibleToJava<LabelingJobArgs>
Machine Learning labeling job object wrapped into ARM resource envelope. API Version: 2020-09-01-preview.
Example Usage
Create or update LabelingJob
using System.Collections.Generic;
using System.Linq;
using Pulumi;
using AzureNative = Pulumi.AzureNative;
return await Deployment.RunAsync(() =>
{
var labelingJob = new AzureNative.MachineLearningServices.LabelingJob("labelingJob", new()
{
LabelingJobId = "testLabelingJob",
Properties = new AzureNative.MachineLearningServices.Inputs.LabelingJobPropertiesArgs
{
DatasetConfiguration = new AzureNative.MachineLearningServices.Inputs.LabelingDatasetConfigurationArgs
{
AssetName = "testdataasset",
DatasetVersion = "1",
EnableIncrementalDatasetRefresh = true,
},
JobInstructions = new AzureNative.MachineLearningServices.Inputs.LabelingJobInstructionsArgs
{
Uri = "https://www.testjobInstructions.com/labeling1.txt",
},
LabelCategories =
{
{ "testCategory", new AzureNative.MachineLearningServices.Inputs.LabelCategoryArgs
{
AllowMultiSelect = false,
Classes =
{
{ "testClass1", new AzureNative.MachineLearningServices.Inputs.LabelClassArgs
{
DisplayName = "testClass1",
Subclasses =
{
{ "testclass1-1", new AzureNative.MachineLearningServices.Inputs.LabelClassArgs
{
DisplayName = "testClass1-1",
} },
},
} },
{ "testClass2", new AzureNative.MachineLearningServices.Inputs.LabelClassArgs
{
DisplayName = "testClass2",
} },
},
DisplayName = "testCategory",
} },
},
LabelingJobMediaProperties = new AzureNative.MachineLearningServices.Inputs.LabelingJobImagePropertiesArgs
{
AnnotationType = "BoundingBox",
MediaType = "Image",
},
MlAssistConfiguration = new AzureNative.MachineLearningServices.Inputs.MLAssistConfigurationArgs
{
InferencingComputeBinding = new AzureNative.MachineLearningServices.Inputs.ComputeBindingArgs
{
ComputeId = "inferencingcompute",
},
MlAssistEnabled = true,
ModelNamePrefix = "testmodel_1",
PrelabelAccuracyThreshold = 0.8,
TrainingComputeBinding = new AzureNative.MachineLearningServices.Inputs.ComputeBindingArgs
{
ComputeId = "trainingcompute",
},
},
Properties =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
Tags =
{
{ "additionalProp1", "string" },
{ "additionalProp2", "string" },
{ "additionalProp3", "string" },
},
},
ResourceGroupName = "workspace-1234",
WorkspaceName = "testworkspace",
});
});Content copied to clipboard
package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.azurenative.machinelearningservices.LabelingJob;
import com.pulumi.azurenative.machinelearningservices.LabelingJobArgs;
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 labelingJob = new LabelingJob("labelingJob", LabelingJobArgs.builder()
.labelingJobId("testLabelingJob")
.properties(Map.ofEntries(
Map.entry("datasetConfiguration", Map.ofEntries(
Map.entry("assetName", "testdataasset"),
Map.entry("datasetVersion", "1"),
Map.entry("enableIncrementalDatasetRefresh", true)
)),
Map.entry("jobInstructions", Map.of("uri", "https://www.testjobInstructions.com/labeling1.txt")),
Map.entry("labelCategories", Map.of("testCategory", Map.ofEntries(
Map.entry("allowMultiSelect", false),
Map.entry("classes", Map.ofEntries(
Map.entry("testClass1", Map.ofEntries(
Map.entry("displayName", "testClass1"),
Map.entry("subclasses", Map.of("testclass1-1", Map.of("displayName", "testClass1-1")))
)),
Map.entry("testClass2", Map.of("displayName", "testClass2"))
)),
Map.entry("displayName", "testCategory")
))),
Map.entry("labelingJobMediaProperties", Map.ofEntries(
Map.entry("annotationType", "BoundingBox"),
Map.entry("mediaType", "Image")
)),
Map.entry("mlAssistConfiguration", Map.ofEntries(
Map.entry("inferencingComputeBinding", Map.of("computeId", "inferencingcompute")),
Map.entry("mlAssistEnabled", true),
Map.entry("modelNamePrefix", "testmodel_1"),
Map.entry("prelabelAccuracyThreshold", 0.8),
Map.entry("trainingComputeBinding", Map.of("computeId", "trainingcompute"))
)),
Map.entry("properties", Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
)),
Map.entry("tags", Map.ofEntries(
Map.entry("additionalProp1", "string"),
Map.entry("additionalProp2", "string"),
Map.entry("additionalProp3", "string")
))
))
.resourceGroupName("workspace-1234")
.workspaceName("testworkspace")
.build());
}
}Content copied to clipboard
Import
An existing resource can be imported using its type token, name, and identifier, e.g.
$ pulumi import azure-native:machinelearningservices:LabelingJob testLabelingJob /subscriptions/00000000-1111-2222-3333-444444444444/resourceGroups/workspace-1234/providers/Microsoft.MachineLearningServices/workspaces/testworkspace/labelingJobs/testLabelingJobContent copied to clipboard
Constructors
Link copied to clipboard
constructor(labelingJobId: Output<String>? = null, properties: Output<LabelingJobPropertiesArgs>? = null, resourceGroupName: Output<String>? = null, workspaceName: Output<String>? = null)