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DataRobot v0.8.15 published on Friday, Mar 14, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.RegisteredModelFromLeaderboard

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DataRobot v0.8.15 published on Friday, Mar 14, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

    registered model from leaderboard

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
import * as datarobot from "@datarobot/pulumi-datarobot";

const example = new datarobot.RegisteredModelFromLeaderboard("example", {
    modelId: "111111111111",
    description: "example description",
    versionName: "example version name",
    predictionThreshold: 0.5,
    computeAllTsIntervals: true,
    distributionPredictionModelId: "222222222222",
    useCaseIds: [datarobot_use_case.example.id],
});
export const datarobotRegisteredModelFromLeaderboardId = example.id;
export const datarobotRegisteredModelFromLeaderboardVersionId = example.versionId;

    import pulumi
import pulumi_datarobot as datarobot

example = datarobot.RegisteredModelFromLeaderboard("example",
    model_id="111111111111",
    description="example description",
    version_name="example version name",
    prediction_threshold=0.5,
    compute_all_ts_intervals=True,
    distribution_prediction_model_id="222222222222",
    use_case_ids=[datarobot_use_case["example"]["id"]])
pulumi.export("datarobotRegisteredModelFromLeaderboardId", example.id)
pulumi.export("datarobotRegisteredModelFromLeaderboardVersionId", example.version_id)

    package main

import (
	"github.com/datarobot-community/pulumi-datarobot/sdk/go/datarobot"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		example, err := datarobot.NewRegisteredModelFromLeaderboard(ctx, "example", &datarobot.RegisteredModelFromLeaderboardArgs{
			ModelId:                       pulumi.String("111111111111"),
			Description:                   pulumi.String("example description"),
			VersionName:                   pulumi.String("example version name"),
			PredictionThreshold:           pulumi.Float64(0.5),
			ComputeAllTsIntervals:         pulumi.Bool(true),
			DistributionPredictionModelId: pulumi.String("222222222222"),
			UseCaseIds: pulumi.StringArray{
				datarobot_use_case.Example.Id,
			},
		})
		if err != nil {
			return err
		}
		ctx.Export("datarobotRegisteredModelFromLeaderboardId", example.ID())
		ctx.Export("datarobotRegisteredModelFromLeaderboardVersionId", example.VersionId)
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Datarobot = DataRobotPulumi.Datarobot;

return await Deployment.RunAsync(() => 
{
    var example = new Datarobot.RegisteredModelFromLeaderboard("example", new()
    {
        ModelId = "111111111111",
        Description = "example description",
        VersionName = "example version name",
        PredictionThreshold = 0.5,
        ComputeAllTsIntervals = true,
        DistributionPredictionModelId = "222222222222",
        UseCaseIds = new[]
        {
            datarobot_use_case.Example.Id,
        },
    });

    return new Dictionary<string, object?>
    {
        ["datarobotRegisteredModelFromLeaderboardId"] = example.Id,
        ["datarobotRegisteredModelFromLeaderboardVersionId"] = example.VersionId,
    };
});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.RegisteredModelFromLeaderboard;
import com.pulumi.datarobot.RegisteredModelFromLeaderboardArgs;
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 example = new RegisteredModelFromLeaderboard("example", RegisteredModelFromLeaderboardArgs.builder()
            .modelId("111111111111")
            .description("example description")
            .versionName("example version name")
            .predictionThreshold(0.5)
            .computeAllTsIntervals(true)
            .distributionPredictionModelId("222222222222")
            .useCaseIds(datarobot_use_case.example().id())
            .build());

        ctx.export("datarobotRegisteredModelFromLeaderboardId", example.id());
        ctx.export("datarobotRegisteredModelFromLeaderboardVersionId", example.versionId());
    }
}

    resources:
  example:
    type: datarobot:RegisteredModelFromLeaderboard
    properties:
      modelId: '111111111111'
      # Optional
      description: example description
      versionName: example version name
      predictionThreshold: 0.5
      computeAllTsIntervals: true
      distributionPredictionModelId: '222222222222'
      useCaseIds:
        - ${datarobot_use_case.example.id}
outputs:
  datarobotRegisteredModelFromLeaderboardId: ${example.id}
  datarobotRegisteredModelFromLeaderboardVersionId: ${example.versionId}

    Create RegisteredModelFromLeaderboard Resource

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

    Constructor syntax

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

@overload
def RegisteredModelFromLeaderboard(resource_name: str,
                                   opts: Optional[ResourceOptions] = None,
                                   model_id: Optional[str] = None,
                                   compute_all_ts_intervals: Optional[bool] = None,
                                   description: Optional[str] = None,
                                   distribution_prediction_model_id: Optional[str] = None,
                                   name: Optional[str] = None,
                                   prediction_threshold: Optional[float] = None,
                                   use_case_ids: Optional[Sequence[str]] = None,
                                   version_name: Optional[str] = None)
    func NewRegisteredModelFromLeaderboard(ctx *Context, name string, args RegisteredModelFromLeaderboardArgs, opts ...ResourceOption) (*RegisteredModelFromLeaderboard, error)
    public RegisteredModelFromLeaderboard(string name, RegisteredModelFromLeaderboardArgs args, CustomResourceOptions? opts = null)
    public RegisteredModelFromLeaderboard(String name, RegisteredModelFromLeaderboardArgs args)
public RegisteredModelFromLeaderboard(String name, RegisteredModelFromLeaderboardArgs args, CustomResourceOptions options)

    type: datarobot:RegisteredModelFromLeaderboard
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 RegisteredModelFromLeaderboardArgs
    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 RegisteredModelFromLeaderboardArgs
    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 RegisteredModelFromLeaderboardArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args RegisteredModelFromLeaderboardArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args RegisteredModelFromLeaderboardArgs
    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 registeredModelFromLeaderboardResource = new Datarobot.RegisteredModelFromLeaderboard("registeredModelFromLeaderboardResource", new()
{
    ModelId = "string",
    ComputeAllTsIntervals = false,
    Description = "string",
    DistributionPredictionModelId = "string",
    Name = "string",
    PredictionThreshold = 0,
    UseCaseIds = new[]
    {
        "string",
    },
    VersionName = "string",
});

    example, err := datarobot.NewRegisteredModelFromLeaderboard(ctx, "registeredModelFromLeaderboardResource", &datarobot.RegisteredModelFromLeaderboardArgs{
	ModelId:                       pulumi.String("string"),
	ComputeAllTsIntervals:         pulumi.Bool(false),
	Description:                   pulumi.String("string"),
	DistributionPredictionModelId: pulumi.String("string"),
	Name:                          pulumi.String("string"),
	PredictionThreshold:           pulumi.Float64(0),
	UseCaseIds: pulumi.StringArray{
		pulumi.String("string"),
	},
	VersionName: pulumi.String("string"),
})

    var registeredModelFromLeaderboardResource = new RegisteredModelFromLeaderboard("registeredModelFromLeaderboardResource", RegisteredModelFromLeaderboardArgs.builder()
    .modelId("string")
    .computeAllTsIntervals(false)
    .description("string")
    .distributionPredictionModelId("string")
    .name("string")
    .predictionThreshold(0)
    .useCaseIds("string")
    .versionName("string")
    .build());

    registered_model_from_leaderboard_resource = datarobot.RegisteredModelFromLeaderboard("registeredModelFromLeaderboardResource",
    model_id="string",
    compute_all_ts_intervals=False,
    description="string",
    distribution_prediction_model_id="string",
    name="string",
    prediction_threshold=0,
    use_case_ids=["string"],
    version_name="string")

    const registeredModelFromLeaderboardResource = new datarobot.RegisteredModelFromLeaderboard("registeredModelFromLeaderboardResource", {
    modelId: "string",
    computeAllTsIntervals: false,
    description: "string",
    distributionPredictionModelId: "string",
    name: "string",
    predictionThreshold: 0,
    useCaseIds: ["string"],
    versionName: "string",
});

    type: datarobot:RegisteredModelFromLeaderboard
properties:
    computeAllTsIntervals: false
    description: string
    distributionPredictionModelId: string
    modelId: string
    name: string
    predictionThreshold: 0
    useCaseIds:
        - string
    versionName: string

    RegisteredModelFromLeaderboard 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 RegisteredModelFromLeaderboard resource accepts the following input properties:

    ModelId string
    The ID of the DataRobot model for this Registered Model.
    ComputeAllTsIntervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    Description string
    The description of the Registered Model.
    DistributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    Name string
    The name of the Registered Model.
    PredictionThreshold double
    The prediction threshold for the model.
    UseCaseIds List<string>
    The list of Use Case IDs to add the Registered Model version to.
    VersionName string
    The name of the Registered Model Version.
    ModelId string
    The ID of the DataRobot model for this Registered Model.
    ComputeAllTsIntervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    Description string
    The description of the Registered Model.
    DistributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    Name string
    The name of the Registered Model.
    PredictionThreshold float64
    The prediction threshold for the model.
    UseCaseIds []string
    The list of Use Case IDs to add the Registered Model version to.
    VersionName string
    The name of the Registered Model Version.
    modelId String
    The ID of the DataRobot model for this Registered Model.
    computeAllTsIntervals Boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description String
    The description of the Registered Model.
    distributionPredictionModelId String
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    name String
    The name of the Registered Model.
    predictionThreshold Double
    The prediction threshold for the model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Registered Model version to.
    versionName String
    The name of the Registered Model Version.
    modelId string
    The ID of the DataRobot model for this Registered Model.
    computeAllTsIntervals boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description string
    The description of the Registered Model.
    distributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    name string
    The name of the Registered Model.
    predictionThreshold number
    The prediction threshold for the model.
    useCaseIds string[]
    The list of Use Case IDs to add the Registered Model version to.
    versionName string
    The name of the Registered Model Version.
    model_id str
    The ID of the DataRobot model for this Registered Model.
    compute_all_ts_intervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    description str
    The description of the Registered Model.
    distribution_prediction_model_id str
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    name str
    The name of the Registered Model.
    prediction_threshold float
    The prediction threshold for the model.
    use_case_ids Sequence[str]
    The list of Use Case IDs to add the Registered Model version to.
    version_name str
    The name of the Registered Model Version.
    modelId String
    The ID of the DataRobot model for this Registered Model.
    computeAllTsIntervals Boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description String
    The description of the Registered Model.
    distributionPredictionModelId String
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    name String
    The name of the Registered Model.
    predictionThreshold Number
    The prediction threshold for the model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Registered Model version to.
    versionName String
    The name of the Registered Model Version.

    Outputs

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

    Id string
    The provider-assigned unique ID for this managed resource.
    VersionId string
    The ID of the Registered Model Version.
    Id string
    The provider-assigned unique ID for this managed resource.
    VersionId string
    The ID of the Registered Model Version.
    id String
    The provider-assigned unique ID for this managed resource.
    versionId String
    The ID of the Registered Model Version.
    id string
    The provider-assigned unique ID for this managed resource.
    versionId string
    The ID of the Registered Model Version.
    id str
    The provider-assigned unique ID for this managed resource.
    version_id str
    The ID of the Registered Model Version.
    id String
    The provider-assigned unique ID for this managed resource.
    versionId String
    The ID of the Registered Model Version.

    Look up Existing RegisteredModelFromLeaderboard Resource

    Get an existing RegisteredModelFromLeaderboard 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?: RegisteredModelFromLeaderboardState, opts?: CustomResourceOptions): RegisteredModelFromLeaderboard
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        compute_all_ts_intervals: Optional[bool] = None,
        description: Optional[str] = None,
        distribution_prediction_model_id: Optional[str] = None,
        model_id: Optional[str] = None,
        name: Optional[str] = None,
        prediction_threshold: Optional[float] = None,
        use_case_ids: Optional[Sequence[str]] = None,
        version_id: Optional[str] = None,
        version_name: Optional[str] = None) -> RegisteredModelFromLeaderboard
    func GetRegisteredModelFromLeaderboard(ctx *Context, name string, id IDInput, state *RegisteredModelFromLeaderboardState, opts ...ResourceOption) (*RegisteredModelFromLeaderboard, error)
    public static RegisteredModelFromLeaderboard Get(string name, Input<string> id, RegisteredModelFromLeaderboardState? state, CustomResourceOptions? opts = null)
    public static RegisteredModelFromLeaderboard get(String name, Output<String> id, RegisteredModelFromLeaderboardState state, CustomResourceOptions options)
    resources:  _:    type: datarobot:RegisteredModelFromLeaderboard    get:      id: ${id}
    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:
    ComputeAllTsIntervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    Description string
    The description of the Registered Model.
    DistributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    ModelId string
    The ID of the DataRobot model for this Registered Model.
    Name string
    The name of the Registered Model.
    PredictionThreshold double
    The prediction threshold for the model.
    UseCaseIds List<string>
    The list of Use Case IDs to add the Registered Model version to.
    VersionId string
    The ID of the Registered Model Version.
    VersionName string
    The name of the Registered Model Version.
    ComputeAllTsIntervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    Description string
    The description of the Registered Model.
    DistributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    ModelId string
    The ID of the DataRobot model for this Registered Model.
    Name string
    The name of the Registered Model.
    PredictionThreshold float64
    The prediction threshold for the model.
    UseCaseIds []string
    The list of Use Case IDs to add the Registered Model version to.
    VersionId string
    The ID of the Registered Model Version.
    VersionName string
    The name of the Registered Model Version.
    computeAllTsIntervals Boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description String
    The description of the Registered Model.
    distributionPredictionModelId String
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    modelId String
    The ID of the DataRobot model for this Registered Model.
    name String
    The name of the Registered Model.
    predictionThreshold Double
    The prediction threshold for the model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Registered Model version to.
    versionId String
    The ID of the Registered Model Version.
    versionName String
    The name of the Registered Model Version.
    computeAllTsIntervals boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description string
    The description of the Registered Model.
    distributionPredictionModelId string
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    modelId string
    The ID of the DataRobot model for this Registered Model.
    name string
    The name of the Registered Model.
    predictionThreshold number
    The prediction threshold for the model.
    useCaseIds string[]
    The list of Use Case IDs to add the Registered Model version to.
    versionId string
    The ID of the Registered Model Version.
    versionName string
    The name of the Registered Model Version.
    compute_all_ts_intervals bool
    Whether to compute all time series intervals (1-100 percentiles).
    description str
    The description of the Registered Model.
    distribution_prediction_model_id str
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    model_id str
    The ID of the DataRobot model for this Registered Model.
    name str
    The name of the Registered Model.
    prediction_threshold float
    The prediction threshold for the model.
    use_case_ids Sequence[str]
    The list of Use Case IDs to add the Registered Model version to.
    version_id str
    The ID of the Registered Model Version.
    version_name str
    The name of the Registered Model Version.
    computeAllTsIntervals Boolean
    Whether to compute all time series intervals (1-100 percentiles).
    description String
    The description of the Registered Model.
    distributionPredictionModelId String
    The ID of the DataRobot distribution prediction model trained on predictions from the DataRobot model.
    modelId String
    The ID of the DataRobot model for this Registered Model.
    name String
    The name of the Registered Model.
    predictionThreshold Number
    The prediction threshold for the model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Registered Model version to.
    versionId String
    The ID of the Registered Model Version.
    versionName String
    The name of the Registered Model Version.

    Package Details

    Repository
    datarobot datarobot-community/pulumi-datarobot
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the datarobot Terraform Provider.
    datarobot logo
    DataRobot v0.8.15 published on Friday, Mar 14, 2025 by DataRobot, Inc.
    datarobot-community/pulumi-datarobot