EngineModel

class EngineModel : KotlinCustomResource

Represents a machine learning solution. A model can have multiple versions, each of which is a deployed, trained model ready to receive prediction requests. The model itself is just a container. To get more information about Model, see:

Example Usage

Ml Model Basic

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.ml.EngineModel;
import com.pulumi.gcp.ml.EngineModelArgs;
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 default_ = new EngineModel("default", EngineModelArgs.builder()
.description("My model")
.regions("us-central1")
.build());
}
}

Ml Model Full

package generated_program;
import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.gcp.ml.EngineModel;
import com.pulumi.gcp.ml.EngineModelArgs;
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 default_ = new EngineModel("default", EngineModelArgs.builder()
.description("My model")
.labels(Map.of("my_model", "foo"))
.onlinePredictionConsoleLogging(true)
.onlinePredictionLogging(true)
.regions("us-central1")
.build());
}
}

Import

Model can be imported using any of these accepted formats

$ pulumi import gcp:ml/engineModel:EngineModel default projects/{{project}}/models/{{name}}
$ pulumi import gcp:ml/engineModel:EngineModel default {{project}}/{{name}}
$ pulumi import gcp:ml/engineModel:EngineModel default {{name}}

Properties

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The default version of the model. This version will be used to handle prediction requests that do not specify a version. Structure is documented below.

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val description: Output<String>?

The description specified for the model when it was created.

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val id: Output<String>
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val labels: Output<Map<String, String>>?

One or more labels that you can add, to organize your models.

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val name: Output<String>

The name specified for the model.

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If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging

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If true, online prediction access logs are sent to StackDriver Logging.

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val project: Output<String>

The ID of the project in which the resource belongs. If it is not provided, the provider project is used.

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val pulumiChildResources: Set<KotlinResource>
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val regions: Output<String>?

The list of regions where the model is going to be deployed. Currently only one region per model is supported

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val urn: Output<String>