software.amazon.awscdk.services.sagemaker

Interface CfnModel.ContainerDefinitionProperty

All Superinterfaces:

software.amazon.jsii.JsiiSerializable

All Known Implementing Classes:

CfnModel.ContainerDefinitionProperty.Jsii$Proxy

Enclosing class:

CfnModel

@Stability(value=Stable)
public static interface CfnModel.ContainerDefinitionProperty
extends software.amazon.jsii.JsiiSerializable

Describes the container, as part of model definition.

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;
 ContainerDefinitionProperty containerDefinitionProperty = 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();
 

Nested Class Summary

Nested Classes

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

Method Summary

Modifier and Type	Method and Description
static CfnModel.ContainerDefinitionProperty.Builder	builder()
default String	getContainerHostname() This parameter is ignored for models that contain only a `PrimaryContainer` .
default Object	getEnvironment() The environment variables to set in the Docker container.
default String	getImage() The path where inference code is stored.
default Object	getImageConfig() Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).
default String	getInferenceSpecificationName() `CfnModel.ContainerDefinitionProperty.InferenceSpecificationName`.
default String	getMode() Whether the container hosts a single model or multiple models.
default String	getModelDataUrl() The S3 path where the model artifacts, which result from model training, are stored.
default String	getModelPackageName() The name or Amazon Resource Name (ARN) of the model package to use to create the model.
default Object	getMultiModelConfig() Specifies additional configuration for multi-model endpoints.

Methods inherited from interface software.amazon.jsii.JsiiSerializable

$jsii$toJson

Method Detail

getContainerHostname

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

This parameter is ignored for models that contain only a `PrimaryContainer` .

When a ContainerDefinition is part of an inference pipeline, the value of the parameter uniquely identifies the container for the purposes of logging and metrics. For information, see Use Logs and Metrics to Monitor an Inference Pipeline . If you don't specify a value for this parameter for a ContainerDefinition that is part of an inference pipeline, a unique name is automatically assigned based on the position of the ContainerDefinition in the pipeline. If you specify a value for the ContainerHostName for any ContainerDefinition that is part of an inference pipeline, you must specify a value for the ContainerHostName parameter of every ContainerDefinition in that pipeline.

getEnvironment

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

The environment variables to set in the Docker container.

Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.

getImage

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

The path where inference code is stored.

This can be either in Amazon EC2 Container Registry or in a Docker registry that is accessible from the same VPC that you configure for your endpoint. If you are using your own custom algorithm instead of an algorithm provided by SageMaker, the inference code must meet SageMaker requirements. SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker

getImageConfig

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

Specifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).

For information about storing containers in a private Docker registry, see Use a Private Docker Registry for Real-Time Inference Containers

getInferenceSpecificationName

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

`CfnModel.ContainerDefinitionProperty.InferenceSpecificationName`.

getMode

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

Whether the container hosts a single model or multiple models.

getModelDataUrl

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

The S3 path where the model artifacts, which result from model training, are stored.

This path must point to a single gzip compressed tar archive (.tar.gz suffix). The S3 path is required for SageMaker built-in algorithms, but not if you use your own algorithms. For more information on built-in algorithms, see Common Parameters .

The model artifacts must be in an S3 bucket that is in the same region as the model or endpoint you are creating.

If you provide a value for this parameter, SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provide. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS in an AWS Region in the AWS Identity and Access Management User Guide .

If you use a built-in algorithm to create a model, SageMaker requires that you provide a S3 path to the model artifacts in ModelDataUrl .

getModelPackageName

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

The name or Amazon Resource Name (ARN) of the model package to use to create the model.

getMultiModelConfig

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

Specifies additional configuration for multi-model endpoints.

builder

@Stability(value=Stable)
static CfnModel.ContainerDefinitionProperty.Builder builder()

Returns:

a CfnModel.ContainerDefinitionProperty.Builder of CfnModel.ContainerDefinitionProperty