@pulumi/aws-native
Version:
The Pulumi AWS Cloud Control Provider enables you to build, deploy, and manage [any AWS resource that's supported by the AWS Cloud Control API](https://github.com/pulumi/pulumi-aws-native/blob/master/provider/cmd/pulumi-gen-aws-native/supported-types.txt)
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TypeScript
import * as pulumi from "@pulumi/pulumi";
import * as inputs from "../types/input";
import * as outputs from "../types/output";
/**
* Resource type definition for AWS::SageMaker::Model
*/
export declare class Model extends pulumi.CustomResource {
/**
* Get an existing Model resource's state with the given name, ID, and optional extra
* properties used to qualify the lookup.
*
* @param name The _unique_ name of the resulting resource.
* @param id The _unique_ provider ID of the resource to lookup.
* @param opts Optional settings to control the behavior of the CustomResource.
*/
static get(name: string, id: pulumi.Input<pulumi.ID>, opts?: pulumi.CustomResourceOptions): Model;
/**
* Returns true if the given object is an instance of Model. This is designed to work even
* when multiple copies of the Pulumi SDK have been loaded into the same process.
*/
static isInstance(obj: any): obj is Model;
/**
* Specifies the containers in the inference pipeline.
*/
readonly containers: pulumi.Output<outputs.sagemaker.ModelContainerDefinition[] | undefined>;
/**
* Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
*/
readonly enableNetworkIsolation: pulumi.Output<boolean | undefined>;
/**
* The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
*/
readonly executionRoleArn: pulumi.Output<string | undefined>;
/**
* Specifies details of how containers in a multi-container endpoint are called.
*/
readonly inferenceExecutionConfig: pulumi.Output<outputs.sagemaker.ModelInferenceExecutionConfig | undefined>;
/**
* The Amazon Resource Name (ARN) of the model.
*/
readonly modelArn: pulumi.Output<string>;
/**
* The name of the new model.
*/
readonly modelName: pulumi.Output<string | undefined>;
/**
* The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
*/
readonly primaryContainer: pulumi.Output<outputs.sagemaker.ModelContainerDefinition | undefined>;
/**
* An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see [Tagging AWS Resources](https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
*/
readonly tags: pulumi.Output<outputs.Tag[] | undefined>;
/**
* A [VpcConfig](https://docs.aws.amazon.com/sagemaker/latest/dg/API_VpcConfig.html) object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. `VpcConfig` is used in hosting services and in batch transform. For more information, see [Protect Endpoints by Using an Amazon Virtual Private Cloud](https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html) and [Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud](https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.html) .
*/
readonly vpcConfig: pulumi.Output<outputs.sagemaker.ModelVpcConfig | undefined>;
/**
* Create a Model resource with the given unique name, arguments, and options.
*
* @param name The _unique_ name of the resource.
* @param args The arguments to use to populate this resource's properties.
* @param opts A bag of options that control this resource's behavior.
*/
constructor(name: string, args?: ModelArgs, opts?: pulumi.CustomResourceOptions);
}
/**
* The set of arguments for constructing a Model resource.
*/
export interface ModelArgs {
/**
* Specifies the containers in the inference pipeline.
*/
containers?: pulumi.Input<pulumi.Input<inputs.sagemaker.ModelContainerDefinitionArgs>[]>;
/**
* Isolates the model container. No inbound or outbound network calls can be made to or from the model container.
*/
enableNetworkIsolation?: pulumi.Input<boolean>;
/**
* The Amazon Resource Name (ARN) of the IAM role that you specified for the model.
*/
executionRoleArn?: pulumi.Input<string>;
/**
* Specifies details of how containers in a multi-container endpoint are called.
*/
inferenceExecutionConfig?: pulumi.Input<inputs.sagemaker.ModelInferenceExecutionConfigArgs>;
/**
* The name of the new model.
*/
modelName?: pulumi.Input<string>;
/**
* The location of the primary docker image containing inference code, associated artifacts, and custom environment map that the inference code uses when the model is deployed for predictions.
*/
primaryContainer?: pulumi.Input<inputs.sagemaker.ModelContainerDefinitionArgs>;
/**
* An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see [Tagging AWS Resources](https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html).
*/
tags?: pulumi.Input<pulumi.Input<inputs.TagArgs>[]>;
/**
* A [VpcConfig](https://docs.aws.amazon.com/sagemaker/latest/dg/API_VpcConfig.html) object that specifies the VPC that you want your model to connect to. Control access to and from your model container by configuring the VPC. `VpcConfig` is used in hosting services and in batch transform. For more information, see [Protect Endpoints by Using an Amazon Virtual Private Cloud](https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html) and [Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private Cloud](https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.html) .
*/
vpcConfig?: pulumi.Input<inputs.sagemaker.ModelVpcConfigArgs>;
}