sagemaker/aws.sdk.kotlin.services.sagemaker.model/ContainerDefinition/Builder

Builder

Properties

var additionalModelDataSources: List<AdditionalModelDataSource>?

Data sources that are available to your model in addition to the one that you specify for ModelDataSource when you use the CreateModel action.

containerHostname

var containerHostname: String?

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

environment

var environment: Map<String, String>?

The environment variables to set in the Docker container. Don't include any sensitive data in your environment variables.

image

var image: String?

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.

imageConfig

var imageConfig: 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.

inferenceSpecificationName

var inferenceSpecificationName: String?

The inference specification name in the model package version.

mode

var mode: ContainerMode?

Whether the container hosts a single model or multiple models.

modelDataSource

var modelDataSource: ModelDataSource?

Specifies the location of ML model data to deploy.

modelDataUrl

var modelDataUrl: String?

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.

modelPackageName

var modelPackageName: String?

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

multiModelConfig

var multiModelConfig: MultiModelConfig?

Specifies additional configuration for multi-model endpoints.

Functions

imageConfig

fun imageConfig(block: ImageConfig.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.ImageConfig inside the given block

modelDataSource

fun modelDataSource(block: ModelDataSource.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.ModelDataSource inside the given block

multiModelConfig

fun multiModelConfig(block: MultiModelConfig.Builder.() -> Unit)

construct an aws.sdk.kotlin.services.sagemaker.model.MultiModelConfig inside the given block