Package software.amazon.awscdk.services.sagemaker

Class CfnModel.ContainerDefinitionProperty.Builder

java.lang.Object

software.amazon.awscdk.services.sagemaker.CfnModel.ContainerDefinitionProperty.Builder

All Implemented Interfaces:

software.amazon.jsii.Builder<CfnModel.ContainerDefinitionProperty>

Enclosing interface:

CfnModel.ContainerDefinitionProperty

@Stability(Stable)
public static final class CfnModel.ContainerDefinitionProperty.Builder
extends Object
implements software.amazon.jsii.Builder<CfnModel.ContainerDefinitionProperty>

A builder for CfnModel.ContainerDefinitionProperty

Constructor Summary

Constructors

Constructor	Description
Builder()

Method Summary

Modifier and Type	Method	Description
CfnModel.ContainerDefinitionProperty	build()	Builds the configured instance.
CfnModel.ContainerDefinitionProperty.Builder	containerHostname(String containerHostname)	Sets the value of CfnModel.ContainerDefinitionProperty.getContainerHostname()
CfnModel.ContainerDefinitionProperty.Builder	environment(Object environment)	Sets the value of CfnModel.ContainerDefinitionProperty.getEnvironment()
CfnModel.ContainerDefinitionProperty.Builder	image(String image)	Sets the value of CfnModel.ContainerDefinitionProperty.getImage()
CfnModel.ContainerDefinitionProperty.Builder	imageConfig(IResolvable imageConfig)	Sets the value of CfnModel.ContainerDefinitionProperty.getImageConfig()
CfnModel.ContainerDefinitionProperty.Builder	imageConfig(CfnModel.ImageConfigProperty imageConfig)	Sets the value of CfnModel.ContainerDefinitionProperty.getImageConfig()
CfnModel.ContainerDefinitionProperty.Builder	inferenceSpecificationName(String inferenceSpecificationName)	Sets the value of CfnModel.ContainerDefinitionProperty.getInferenceSpecificationName()
CfnModel.ContainerDefinitionProperty.Builder	mode(String mode)	Sets the value of CfnModel.ContainerDefinitionProperty.getMode()
CfnModel.ContainerDefinitionProperty.Builder	modelDataUrl(String modelDataUrl)	Sets the value of CfnModel.ContainerDefinitionProperty.getModelDataUrl()
CfnModel.ContainerDefinitionProperty.Builder	modelPackageName(String modelPackageName)	Sets the value of CfnModel.ContainerDefinitionProperty.getModelPackageName()
CfnModel.ContainerDefinitionProperty.Builder	multiModelConfig(IResolvable multiModelConfig)	Sets the value of CfnModel.ContainerDefinitionProperty.getMultiModelConfig()
CfnModel.ContainerDefinitionProperty.Builder	multiModelConfig(CfnModel.MultiModelConfigProperty multiModelConfig)	Sets the value of CfnModel.ContainerDefinitionProperty.getMultiModelConfig()

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Details

Builder

public Builder()

Method Details

containerHostname

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder containerHostname(String containerHostname)

Sets the value of CfnModel.ContainerDefinitionProperty.getContainerHostname()

Parameters:

containerHostname - 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.

Returns:

this

environment

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder environment(Object environment)

Sets the value of CfnModel.ContainerDefinitionProperty.getEnvironment()

Parameters:

environment - 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.

Returns:

this

image

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder image(String image)

Sets the value of CfnModel.ContainerDefinitionProperty.getImage()

Parameters:

image - 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 .

The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.

Returns:

this

imageConfig

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder imageConfig(IResolvable imageConfig)

Sets the value of CfnModel.ContainerDefinitionProperty.getImageConfig()

Parameters:

imageConfig - 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 .

The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.

Returns:

this

imageConfig

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder imageConfig(CfnModel.ImageConfigProperty imageConfig)

Sets the value of CfnModel.ContainerDefinitionProperty.getImageConfig()

Parameters:

imageConfig - 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 .

The model artifacts in an Amazon S3 bucket and the Docker image for inference container in Amazon EC2 Container Registry must be in the same region as the model or endpoint you are creating.

Returns:

this

inferenceSpecificationName

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder inferenceSpecificationName(String inferenceSpecificationName)

Sets the value of CfnModel.ContainerDefinitionProperty.getInferenceSpecificationName()

Parameters:

inferenceSpecificationName - The inference specification name in the model package version.

Returns:

this

mode

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder mode(String mode)

Sets the value of CfnModel.ContainerDefinitionProperty.getMode()

Parameters:

mode - Whether the container hosts a single model or multiple models.

Returns:

this

modelDataUrl

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder modelDataUrl(String modelDataUrl)

Sets the value of CfnModel.ContainerDefinitionProperty.getModelDataUrl()

Parameters:

modelDataUrl - 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 AWS 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 .

Returns:

this

modelPackageName

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder modelPackageName(String modelPackageName)

Sets the value of CfnModel.ContainerDefinitionProperty.getModelPackageName()

Parameters:

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

Returns:

this

multiModelConfig

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder multiModelConfig(IResolvable multiModelConfig)

Sets the value of CfnModel.ContainerDefinitionProperty.getMultiModelConfig()

Parameters:

multiModelConfig - Specifies additional configuration for multi-model endpoints.

Returns:

this

multiModelConfig

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty.Builder multiModelConfig(CfnModel.MultiModelConfigProperty multiModelConfig)

Sets the value of CfnModel.ContainerDefinitionProperty.getMultiModelConfig()

Parameters:

multiModelConfig - Specifies additional configuration for multi-model endpoints.

Returns:

this

build

@Stability(Stable)
public CfnModel.ContainerDefinitionProperty build()

Builds the configured instance.

Specified by:

build in interface software.amazon.jsii.Builder<CfnModel.ContainerDefinitionProperty>

Returns:

a new instance of CfnModel.ContainerDefinitionProperty

Throws:

NullPointerException - if any required attribute was not provided