Engine Model
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:
How-to Guides
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());
}
}
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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());
}
}
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Import
Model can be imported using any of these accepted formats
$ pulumi import gcp:ml/engineModel:EngineModel default projects/{{project}}/models/{{name}}
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$ pulumi import gcp:ml/engineModel:EngineModel default {{project}}/{{name}}
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$ pulumi import gcp:ml/engineModel:EngineModel default {{name}}
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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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The description specified for the model when it was created.
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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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