Model

Provides a SageMaker model resource.

Example Usage

using Pulumi;
using Aws = Pulumi.Aws;

class MyStack : Stack
{
    public MyStack()
    {
        var model = new Aws.Sagemaker.Model("model", new Aws.Sagemaker.ModelArgs
        {
            ExecutionRoleArn = aws_iam_role.Foo.Arn,
            PrimaryContainer = new Aws.Sagemaker.Inputs.ModelPrimaryContainerArgs
            {
                Image = "174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:1",
            },
        });
        var assumeRole = Output.Create(Aws.Iam.GetPolicyDocument.InvokeAsync(new Aws.Iam.GetPolicyDocumentArgs
        {
            Statements = 
            {
                new Aws.Iam.Inputs.GetPolicyDocumentStatementArgs
                {
                    Actions = 
                    {
                        "sts:AssumeRole",
                    },
                    Principals = 
                    {
                        new Aws.Iam.Inputs.GetPolicyDocumentStatementPrincipalArgs
                        {
                            Identifiers = 
                            {
                                "sagemaker.amazonaws.com",
                            },
                            Type = "Service",
                        },
                    },
                },
            },
        }));
        var role = new Aws.Iam.Role("role", new Aws.Iam.RoleArgs
        {
            AssumeRolePolicy = assumeRole.Apply(assumeRole => assumeRole.Json),
        });
    }

}

package main

import (
    "github.com/pulumi/pulumi-aws/sdk/v2/go/aws/iam"
    "github.com/pulumi/pulumi-aws/sdk/v2/go/aws/sagemaker"
    "github.com/pulumi/pulumi/sdk/v2/go/pulumi"
)

func main() {
    pulumi.Run(func(ctx *pulumi.Context) error {
        _, err := sagemaker.NewModel(ctx, "model", &sagemaker.ModelArgs{
            ExecutionRoleArn: pulumi.String(aws_iam_role.Foo.Arn),
            PrimaryContainer: &sagemaker.ModelPrimaryContainerArgs{
                Image: pulumi.String("174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:1"),
            },
        })
        if err != nil {
            return err
        }
        assumeRole, err := iam.GetPolicyDocument(ctx, &iam.GetPolicyDocumentArgs{
            Statements: []iam.GetPolicyDocumentStatement{
                iam.GetPolicyDocumentStatement{
                    Actions: []string{
                        "sts:AssumeRole",
                    },
                    Principals: []iam.GetPolicyDocumentStatementPrincipal{
                        iam.GetPolicyDocumentStatementPrincipal{
                            Identifiers: []string{
                                "sagemaker.amazonaws.com",
                            },
                            Type: "Service",
                        },
                    },
                },
            },
        }, nil)
        if err != nil {
            return err
        }
        _, err = iam.NewRole(ctx, "role", &iam.RoleArgs{
            AssumeRolePolicy: pulumi.String(assumeRole.Json),
        })
        if err != nil {
            return err
        }
        return nil
    })
}

import pulumi
import pulumi_aws as aws

model = aws.sagemaker.Model("model",
    execution_role_arn=aws_iam_role["foo"]["arn"],
    primary_container={
        "image": "174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:1",
    })
assume_role = aws.iam.get_policy_document(statements=[{
    "actions": ["sts:AssumeRole"],
    "principals": [{
        "identifiers": ["sagemaker.amazonaws.com"],
        "type": "Service",
    }],
}])
role = aws.iam.Role("role", assume_role_policy=assume_role.json)

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

const model = new aws.sagemaker.Model("m", {
    executionRoleArn: aws_iam_role_foo.arn,
    primaryContainer: {
        image: "174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:1",
    },
});
const assumeRole = pulumi.output(aws.iam.getPolicyDocument({
    statements: [{
        actions: ["sts:AssumeRole"],
        principals: [{
            identifiers: ["sagemaker.amazonaws.com"],
            type: "Service",
        }],
    }],
}, { async: true }));
const role = new aws.iam.Role("r", {
    assumeRolePolicy: assumeRole.json,
});

Create a Model Resource

new Model(name: string, args: ModelArgs, opts?: CustomResourceOptions);

def Model(resource_name, opts=None, containers=None, enable_network_isolation=None, execution_role_arn=None, name=None, primary_container=None, tags=None, vpc_config=None, __props__=None);

func NewModel(ctx *Context, name string, args ModelArgs, opts ...ResourceOption) (*Model, error)

public Model(string name, ModelArgs args, CustomResourceOptions? opts = null)

name string: The unique name of the resource.
args ModelArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
opts ResourceOptions: A bag of options that control this resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args ModelArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args ModelArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

Model Resource Properties

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

Inputs

The Model resource accepts the following input properties:

ExecutionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
Containers List<ModelContainerArgs>: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
EnableNetworkIsolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
Name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
PrimaryContainer ModelPrimaryContainerArgs: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
Tags Dictionary<string, string>: A map of tags to assign to the resource.
VpcConfig ModelVpcConfigArgs: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

ExecutionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
Containers []ModelContainer: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
EnableNetworkIsolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
Name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
PrimaryContainer ModelPrimaryContainer: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
Tags map[string]string: A map of tags to assign to the resource.
VpcConfig ModelVpcConfig: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

executionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
containers ModelContainer[]: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
enableNetworkIsolation boolean: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
primaryContainer ModelPrimaryContainer: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
tags {[key: string]: string}: A map of tags to assign to the resource.
vpcConfig ModelVpcConfig: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

execution_role_arn str: A role that SageMaker can assume to access model artifacts and docker images for deployment.
containers List[ModelContainer]: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
enable_network_isolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
name str: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
primary_container Dict[ModelPrimaryContainer]: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
tags Dict[str, str]: A map of tags to assign to the resource.
vpc_config Dict[ModelVpcConfig]: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

Outputs

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

Arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
Id string: The provider-assigned unique ID for this managed resource.

Arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
Id string: The provider-assigned unique ID for this managed resource.

arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
id string: The provider-assigned unique ID for this managed resource.

arn str: The Amazon Resource Name (ARN) assigned by AWS to this model.
id str: The provider-assigned unique ID for this managed resource.

Look up an Existing Model Resource

Get an existing Model 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?: ModelState, opts?: CustomResourceOptions): Model

static get(resource_name, id, opts=None, arn=None, containers=None, enable_network_isolation=None, execution_role_arn=None, name=None, primary_container=None, tags=None, vpc_config=None, __props__=None);

func GetModel(ctx *Context, name string, id IDInput, state *ModelState, opts ...ResourceOption) (*Model, error)

public static Model Get(string name, Input<string> id, ModelState? state, CustomResourceOptions? opts = null)

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.

The following state arguments are supported:

Arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
Containers List<ModelContainerArgs>: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
EnableNetworkIsolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
ExecutionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
Name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
PrimaryContainer ModelPrimaryContainerArgs: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
Tags Dictionary<string, string>: A map of tags to assign to the resource.
VpcConfig ModelVpcConfigArgs: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

Arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
Containers []ModelContainer: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
EnableNetworkIsolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
ExecutionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
Name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
PrimaryContainer ModelPrimaryContainer: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
Tags map[string]string: A map of tags to assign to the resource.
VpcConfig ModelVpcConfig: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

arn string: The Amazon Resource Name (ARN) assigned by AWS to this model.
containers ModelContainer[]: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
enableNetworkIsolation boolean: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
executionRoleArn string: A role that SageMaker can assume to access model artifacts and docker images for deployment.
name string: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
primaryContainer ModelPrimaryContainer: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
tags {[key: string]: string}: A map of tags to assign to the resource.
vpcConfig ModelVpcConfig: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

arn str: The Amazon Resource Name (ARN) assigned by AWS to this model.
containers List[ModelContainer]: Specifies containers in the inference pipeline. If not specified, the primary_container argument is required. Fields are documented below.
enable_network_isolation bool: Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
execution_role_arn str: A role that SageMaker can assume to access model artifacts and docker images for deployment.
name str: The name of the model (must be unique). If omitted, this provider will assign a random, unique name.
primary_container Dict[ModelPrimaryContainer]: The primary docker image containing inference code that is used when the model is deployed for predictions. If not specified, the container argument is required. Fields are documented below.
tags Dict[str, str]: A map of tags to assign to the resource.
vpc_config Dict[ModelVpcConfig]: Specifies the VPC that you want your model to connect to. VpcConfig is used in hosting services and in batch transform.

Supporting Types

ModelContainer

See the input and output API doc for this type.

Image string: The registry path where the inference code image is stored in Amazon ECR.
ContainerHostname string: The DNS host name for the container.
Environment Dictionary<string, string>: Environment variables for the Docker container. A list of key value pairs.
ModelDataUrl string: The URL for the S3 location where model artifacts are stored.

Image string: The registry path where the inference code image is stored in Amazon ECR.
ContainerHostname string: The DNS host name for the container.
Environment map[string]string: Environment variables for the Docker container. A list of key value pairs.
ModelDataUrl string: The URL for the S3 location where model artifacts are stored.

image string: The registry path where the inference code image is stored in Amazon ECR.
containerHostname string: The DNS host name for the container.
environment {[key: string]: string}: Environment variables for the Docker container. A list of key value pairs.
modelDataUrl string: The URL for the S3 location where model artifacts are stored.

image str: The registry path where the inference code image is stored in Amazon ECR.
containerHostname str: The DNS host name for the container.
environment Dict[str, str]: Environment variables for the Docker container. A list of key value pairs.
modelDataUrl str: The URL for the S3 location where model artifacts are stored.

ModelPrimaryContainer

See the input and output API doc for this type.

Image string: The registry path where the inference code image is stored in Amazon ECR.
ContainerHostname string: The DNS host name for the container.
Environment Dictionary<string, string>: Environment variables for the Docker container. A list of key value pairs.
ModelDataUrl string: The URL for the S3 location where model artifacts are stored.

Image string: The registry path where the inference code image is stored in Amazon ECR.
ContainerHostname string: The DNS host name for the container.
Environment map[string]string: Environment variables for the Docker container. A list of key value pairs.
ModelDataUrl string: The URL for the S3 location where model artifacts are stored.

image string: The registry path where the inference code image is stored in Amazon ECR.
containerHostname string: The DNS host name for the container.
environment {[key: string]: string}: Environment variables for the Docker container. A list of key value pairs.
modelDataUrl string: The URL for the S3 location where model artifacts are stored.

image str: The registry path where the inference code image is stored in Amazon ECR.
containerHostname str: The DNS host name for the container.
environment Dict[str, str]: Environment variables for the Docker container. A list of key value pairs.
modelDataUrl str: The URL for the S3 location where model artifacts are stored.

ModelVpcConfig

See the input and output API doc for this type.

SecurityGroupIds List<string>
Subnets List<string>

SecurityGroupIds []string
Subnets []string

securityGroupIds string[]
subnets string[]

security_group_ids List[str]
subnets List[str]

Package Details

Repository: https://github.com/pulumi/pulumi-aws
License: Apache-2.0
Notes: This Pulumi package is based on the aws Terraform Provider.

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Model

Example Usage

Create a Model Resource

Model Resource Properties

Inputs

Outputs

Look up an Existing Model Resource

Supporting Types

ModelContainer

ModelPrimaryContainer

ModelVpcConfig

Package Details

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