software.amazon.awscdk.services.sagemaker

Interface CfnModelProps

All Superinterfaces:

software.amazon.jsii.JsiiSerializable

All Known Implementing Classes:

CfnModelProps.Jsii$Proxy

@Generated(value="jsii-pacmak/1.67.0 (build 2c027f5)",
           date="2022-09-19T20:26:41.920Z")
 @Stability(value=Stable)
public interface CfnModelProps
extends software.amazon.jsii.JsiiSerializable

Properties for defining a `CfnModel`.

Example:

 // The code below shows an example of how to instantiate this type.
 // The values are placeholders you should change.
 import software.amazon.awscdk.services.sagemaker.*;
 Object environment;
 CfnModelProps cfnModelProps = CfnModelProps.builder()
         .executionRoleArn("executionRoleArn")
         // the properties below are optional
         .containers(List.of(ContainerDefinitionProperty.builder()
                 .containerHostname("containerHostname")
                 .environment(environment)
                 .image("image")
                 .imageConfig(ImageConfigProperty.builder()
                         .repositoryAccessMode("repositoryAccessMode")
                         // the properties below are optional
                         .repositoryAuthConfig(RepositoryAuthConfigProperty.builder()
                                 .repositoryCredentialsProviderArn("repositoryCredentialsProviderArn")
                                 .build())
                         .build())
                 .inferenceSpecificationName("inferenceSpecificationName")
                 .mode("mode")
                 .modelDataUrl("modelDataUrl")
                 .modelPackageName("modelPackageName")
                 .multiModelConfig(MultiModelConfigProperty.builder()
                         .modelCacheSetting("modelCacheSetting")
                         .build())
                 .build()))
         .enableNetworkIsolation(false)
         .inferenceExecutionConfig(InferenceExecutionConfigProperty.builder()
                 .mode("mode")
                 .build())
         .modelName("modelName")
         .primaryContainer(ContainerDefinitionProperty.builder()
                 .containerHostname("containerHostname")
                 .environment(environment)
                 .image("image")
                 .imageConfig(ImageConfigProperty.builder()
                         .repositoryAccessMode("repositoryAccessMode")
                         // the properties below are optional
                         .repositoryAuthConfig(RepositoryAuthConfigProperty.builder()
                                 .repositoryCredentialsProviderArn("repositoryCredentialsProviderArn")
                                 .build())
                         .build())
                 .inferenceSpecificationName("inferenceSpecificationName")
                 .mode("mode")
                 .modelDataUrl("modelDataUrl")
                 .modelPackageName("modelPackageName")
                 .multiModelConfig(MultiModelConfigProperty.builder()
                         .modelCacheSetting("modelCacheSetting")
                         .build())
                 .build())
         .tags(List.of(CfnTag.builder()
                 .key("key")
                 .value("value")
                 .build()))
         .vpcConfig(VpcConfigProperty.builder()
                 .securityGroupIds(List.of("securityGroupIds"))
                 .subnets(List.of("subnets"))
                 .build())
         .build();
 

Nested Class Summary

Nested Classes

Modifier and Type	Interface and Description
static class	CfnModelProps.Builder A builder for CfnModelProps
static class	CfnModelProps.Jsii$Proxy An implementation for CfnModelProps

Method Summary

Modifier and Type	Method and Description
static CfnModelProps.Builder	builder()
default Object	getContainers() Specifies the containers in the inference pipeline.
default Object	getEnableNetworkIsolation() Isolates the model container.
String	getExecutionRoleArn() The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs.
default Object	getInferenceExecutionConfig() Specifies details of how containers in a multi-container endpoint are called.
default String	getModelName() The name of the new model.
default Object	getPrimaryContainer() 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.
default List<CfnTag>	getTags() A list of key-value pairs to apply to this resource.
default Object	getVpcConfig() 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.

Methods inherited from interface software.amazon.jsii.JsiiSerializable

$jsii$toJson

Method Detail

getExecutionRoleArn

@Stability(value=Stable)
 @NotNull
String getExecutionRoleArn()

The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to access model artifacts and docker image for deployment on ML compute instances or for batch transform jobs.

Deploying on ML compute instances is part of model hosting. For more information, see SageMaker Roles .

To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.

getContainers

@Stability(value=Stable)
 @Nullable
default Object getContainers()

Specifies the containers in the inference pipeline.

getEnableNetworkIsolation

@Stability(value=Stable)
 @Nullable
default Object getEnableNetworkIsolation()

Isolates the model container.

No inbound or outbound network calls can be made to or from the model container.

getInferenceExecutionConfig

@Stability(value=Stable)
 @Nullable
default Object getInferenceExecutionConfig()

Specifies details of how containers in a multi-container endpoint are called.

getModelName

@Stability(value=Stable)
 @Nullable
default String getModelName()

The name of the new model.

getPrimaryContainer

@Stability(value=Stable)
 @Nullable
default Object getPrimaryContainer()

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.

getTags

@Stability(value=Stable)
 @Nullable
default List<CfnTag> getTags()

A list of key-value pairs to apply to this resource.

For more information, see Resource Tag and Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide .

getVpcConfig

@Stability(value=Stable)
 @Nullable
default Object getVpcConfig()

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) .

builder

@Stability(value=Stable)
static CfnModelProps.Builder builder()

Returns:

a CfnModelProps.Builder of CfnModelProps