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Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-gcp

gcp.ml.EngineModel

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Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-gcp

    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

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const _default = new gcp.ml.EngineModel("default", {
    name: "default",
    description: "My model",
    regions: "us-central1",
});

    import pulumi
import pulumi_gcp as gcp

default = gcp.ml.EngineModel("default",
    name="default",
    description="My model",
    regions="us-central1")

    package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/ml"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := ml.NewEngineModel(ctx, "default", &ml.EngineModelArgs{
			Name:        pulumi.String("default"),
			Description: pulumi.String("My model"),
			Regions:     pulumi.String("us-central1"),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var @default = new Gcp.ML.EngineModel("default", new()
    {
        Name = "default",
        Description = "My model",
        Regions = "us-central1",
    });

});

    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()
            .name("default")
            .description("My model")
            .regions("us-central1")
            .build());

    }
}

    resources:
  default:
    type: gcp:ml:EngineModel
    properties:
      name: default
      description: My model
      regions: us-central1

    Ml Model Full

    import * as pulumi from "@pulumi/pulumi";
import * as gcp from "@pulumi/gcp";

const _default = new gcp.ml.EngineModel("default", {
    name: "default",
    description: "My model",
    regions: "us-central1",
    labels: {
        my_model: "foo",
    },
    onlinePredictionLogging: true,
    onlinePredictionConsoleLogging: true,
});

    import pulumi
import pulumi_gcp as gcp

default = gcp.ml.EngineModel("default",
    name="default",
    description="My model",
    regions="us-central1",
    labels={
        "my_model": "foo",
    },
    online_prediction_logging=True,
    online_prediction_console_logging=True)

    package main

import (
	"github.com/pulumi/pulumi-gcp/sdk/v8/go/gcp/ml"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := ml.NewEngineModel(ctx, "default", &ml.EngineModelArgs{
			Name:        pulumi.String("default"),
			Description: pulumi.String("My model"),
			Regions:     pulumi.String("us-central1"),
			Labels: pulumi.StringMap{
				"my_model": pulumi.String("foo"),
			},
			OnlinePredictionLogging:        pulumi.Bool(true),
			OnlinePredictionConsoleLogging: pulumi.Bool(true),
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Gcp = Pulumi.Gcp;

return await Deployment.RunAsync(() => 
{
    var @default = new Gcp.ML.EngineModel("default", new()
    {
        Name = "default",
        Description = "My model",
        Regions = "us-central1",
        Labels = 
        {
            { "my_model", "foo" },
        },
        OnlinePredictionLogging = true,
        OnlinePredictionConsoleLogging = true,
    });

});

    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()
            .name("default")
            .description("My model")
            .regions("us-central1")
            .labels(Map.of("my_model", "foo"))
            .onlinePredictionLogging(true)
            .onlinePredictionConsoleLogging(true)
            .build());

    }
}

    resources:
  default:
    type: gcp:ml:EngineModel
    properties:
      name: default
      description: My model
      regions: us-central1
      labels:
        my_model: foo
      onlinePredictionLogging: true
      onlinePredictionConsoleLogging: true

    Create EngineModel Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new EngineModel(name: string, args?: EngineModelArgs, opts?: CustomResourceOptions);
    @overload
def EngineModel(resource_name: str,
                args: Optional[EngineModelArgs] = None,
                opts: Optional[ResourceOptions] = None)

@overload
def EngineModel(resource_name: str,
                opts: Optional[ResourceOptions] = None,
                default_version: Optional[EngineModelDefaultVersionArgs] = None,
                description: Optional[str] = None,
                labels: Optional[Mapping[str, str]] = None,
                name: Optional[str] = None,
                online_prediction_console_logging: Optional[bool] = None,
                online_prediction_logging: Optional[bool] = None,
                project: Optional[str] = None,
                regions: Optional[str] = None)
    func NewEngineModel(ctx *Context, name string, args *EngineModelArgs, opts ...ResourceOption) (*EngineModel, error)
    public EngineModel(string name, EngineModelArgs? args = null, CustomResourceOptions? opts = null)
    public EngineModel(String name, EngineModelArgs args)
public EngineModel(String name, EngineModelArgs args, CustomResourceOptions options)

    type: gcp:ml:EngineModel
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args EngineModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args EngineModelArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args EngineModelArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args EngineModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args EngineModelArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var engineModelResource = new Gcp.ML.EngineModel("engineModelResource", new()
{
    DefaultVersion = new Gcp.ML.Inputs.EngineModelDefaultVersionArgs
    {
        Name = "string",
    },
    Description = "string",
    Labels = 
    {
        { "string", "string" },
    },
    Name = "string",
    OnlinePredictionConsoleLogging = false,
    OnlinePredictionLogging = false,
    Project = "string",
    Regions = "string",
});

    example, err := ml.NewEngineModel(ctx, "engineModelResource", &ml.EngineModelArgs{
	DefaultVersion: &ml.EngineModelDefaultVersionArgs{
		Name: pulumi.String("string"),
	},
	Description: pulumi.String("string"),
	Labels: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	Name:                           pulumi.String("string"),
	OnlinePredictionConsoleLogging: pulumi.Bool(false),
	OnlinePredictionLogging:        pulumi.Bool(false),
	Project:                        pulumi.String("string"),
	Regions:                        pulumi.String("string"),
})

    var engineModelResource = new EngineModel("engineModelResource", EngineModelArgs.builder()
    .defaultVersion(EngineModelDefaultVersionArgs.builder()
        .name("string")
        .build())
    .description("string")
    .labels(Map.of("string", "string"))
    .name("string")
    .onlinePredictionConsoleLogging(false)
    .onlinePredictionLogging(false)
    .project("string")
    .regions("string")
    .build());

    engine_model_resource = gcp.ml.EngineModel("engineModelResource",
    default_version={
        "name": "string",
    },
    description="string",
    labels={
        "string": "string",
    },
    name="string",
    online_prediction_console_logging=False,
    online_prediction_logging=False,
    project="string",
    regions="string")

    const engineModelResource = new gcp.ml.EngineModel("engineModelResource", {
    defaultVersion: {
        name: "string",
    },
    description: "string",
    labels: {
        string: "string",
    },
    name: "string",
    onlinePredictionConsoleLogging: false,
    onlinePredictionLogging: false,
    project: "string",
    regions: "string",
});

    type: gcp:ml:EngineModel
properties:
    defaultVersion:
        name: string
    description: string
    labels:
        string: string
    name: string
    onlinePredictionConsoleLogging: false
    onlinePredictionLogging: false
    project: string
    regions: string

    EngineModel Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The EngineModel resource accepts the following input properties:

    DefaultVersion EngineModelDefaultVersion
    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.
    Description string
    The description specified for the model when it was created.
    Labels Dictionary<string, string>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    Name string
    The name specified for the model.

    OnlinePredictionConsoleLogging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    OnlinePredictionLogging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    Regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    DefaultVersion EngineModelDefaultVersionArgs
    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.
    Description string
    The description specified for the model when it was created.
    Labels map[string]string
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    Name string
    The name specified for the model.

    OnlinePredictionConsoleLogging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    OnlinePredictionLogging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    Regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion EngineModelDefaultVersion
    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.
    description String
    The description specified for the model when it was created.
    labels Map<String,String>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name String
    The name specified for the model.

    onlinePredictionConsoleLogging Boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging Boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    regions String
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion EngineModelDefaultVersion
    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.
    description string
    The description specified for the model when it was created.
    labels {[key: string]: string}
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name string
    The name specified for the model.

    onlinePredictionConsoleLogging boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    default_version EngineModelDefaultVersionArgs
    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.
    description str
    The description specified for the model when it was created.
    labels Mapping[str, str]
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name str
    The name specified for the model.

    online_prediction_console_logging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    online_prediction_logging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    project str
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    regions str
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion Property Map
    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.
    description String
    The description specified for the model when it was created.
    labels Map<String>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name String
    The name specified for the model.

    onlinePredictionConsoleLogging Boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging Boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    regions String
    The list of regions where the model is going to be deployed. Currently only one region per model is supported

    Outputs

    All input properties are implicitly available as output properties. Additionally, the EngineModel resource produces the following output properties:

    EffectiveLabels Dictionary<string, string>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Id string
    The provider-assigned unique ID for this managed resource.
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    EffectiveLabels map[string]string
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Id string
    The provider-assigned unique ID for this managed resource.
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    effectiveLabels Map<String,String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id String
    The provider-assigned unique ID for this managed resource.
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    effectiveLabels {[key: string]: string}
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id string
    The provider-assigned unique ID for this managed resource.
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    effective_labels Mapping[str, str]
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id str
    The provider-assigned unique ID for this managed resource.
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    id String
    The provider-assigned unique ID for this managed resource.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.

    Look up Existing EngineModel Resource

    Get an existing EngineModel resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: EngineModelState, opts?: CustomResourceOptions): EngineModel
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        default_version: Optional[EngineModelDefaultVersionArgs] = None,
        description: Optional[str] = None,
        effective_labels: Optional[Mapping[str, str]] = None,
        labels: Optional[Mapping[str, str]] = None,
        name: Optional[str] = None,
        online_prediction_console_logging: Optional[bool] = None,
        online_prediction_logging: Optional[bool] = None,
        project: Optional[str] = None,
        pulumi_labels: Optional[Mapping[str, str]] = None,
        regions: Optional[str] = None) -> EngineModel
    func GetEngineModel(ctx *Context, name string, id IDInput, state *EngineModelState, opts ...ResourceOption) (*EngineModel, error)
    public static EngineModel Get(string name, Input<string> id, EngineModelState? state, CustomResourceOptions? opts = null)
    public static EngineModel get(String name, Output<String> id, EngineModelState state, CustomResourceOptions options)
    Resource lookup is not supported in YAML
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    DefaultVersion EngineModelDefaultVersion
    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.
    Description string
    The description specified for the model when it was created.
    EffectiveLabels Dictionary<string, string>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Labels Dictionary<string, string>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    Name string
    The name specified for the model.

    OnlinePredictionConsoleLogging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    OnlinePredictionLogging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels Dictionary<string, string>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    Regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    DefaultVersion EngineModelDefaultVersionArgs
    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.
    Description string
    The description specified for the model when it was created.
    EffectiveLabels map[string]string
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    Labels map[string]string
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    Name string
    The name specified for the model.

    OnlinePredictionConsoleLogging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    OnlinePredictionLogging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    Project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    PulumiLabels map[string]string
    The combination of labels configured directly on the resource and default labels configured on the provider.
    Regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion EngineModelDefaultVersion
    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.
    description String
    The description specified for the model when it was created.
    effectiveLabels Map<String,String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    labels Map<String,String>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name String
    The name specified for the model.

    onlinePredictionConsoleLogging Boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging Boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels Map<String,String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    regions String
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion EngineModelDefaultVersion
    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.
    description string
    The description specified for the model when it was created.
    effectiveLabels {[key: string]: string}
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    labels {[key: string]: string}
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name string
    The name specified for the model.

    onlinePredictionConsoleLogging boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project string
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels {[key: string]: string}
    The combination of labels configured directly on the resource and default labels configured on the provider.
    regions string
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    default_version EngineModelDefaultVersionArgs
    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.
    description str
    The description specified for the model when it was created.
    effective_labels Mapping[str, str]
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    labels Mapping[str, str]
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name str
    The name specified for the model.

    online_prediction_console_logging bool
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    online_prediction_logging bool
    If true, online prediction access logs are sent to StackDriver Logging.
    project str
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumi_labels Mapping[str, str]
    The combination of labels configured directly on the resource and default labels configured on the provider.
    regions str
    The list of regions where the model is going to be deployed. Currently only one region per model is supported
    defaultVersion Property Map
    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.
    description String
    The description specified for the model when it was created.
    effectiveLabels Map<String>
    All of labels (key/value pairs) present on the resource in GCP, including the labels configured through Pulumi, other clients and services.
    labels Map<String>
    One or more labels that you can add, to organize your models. Note: This field is non-authoritative, and will only manage the labels present in your configuration. Please refer to the field effective_labels for all of the labels present on the resource.
    name String
    The name specified for the model.

    onlinePredictionConsoleLogging Boolean
    If true, online prediction nodes send stderr and stdout streams to Stackdriver Logging
    onlinePredictionLogging Boolean
    If true, online prediction access logs are sent to StackDriver Logging.
    project String
    The ID of the project in which the resource belongs. If it is not provided, the provider project is used.
    pulumiLabels Map<String>
    The combination of labels configured directly on the resource and default labels configured on the provider.
    regions String
    The list of regions where the model is going to be deployed. Currently only one region per model is supported

    Supporting Types

    EngineModelDefaultVersion, EngineModelDefaultVersionArgs

    Name string
    The name specified for the version when it was created.
    Name string
    The name specified for the version when it was created.
    name String
    The name specified for the version when it was created.
    name string
    The name specified for the version when it was created.
    name str
    The name specified for the version when it was created.
    name String
    The name specified for the version when it was created.

    Import

    Model can be imported using any of these accepted formats:

    • projects/{{project}}/models/{{name}}

    • {{project}}/{{name}}

    • {{name}}

    When using the pulumi import command, Model can be imported using one of the formats above. For example:

    $ 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}}

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    Google Cloud (GCP) Classic pulumi/pulumi-gcp
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the google-beta Terraform Provider.
    gcp logo
    Google Cloud Classic v8.9.3 published on Monday, Nov 18, 2024 by Pulumi
    pulumi/pulumi-gcp