Interface CfnModelPackage.ModelPackageContainerDefinitionProperty
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnModelPackage.ModelPackageContainerDefinitionProperty.Jsii$Proxy
- Enclosing class:
- CfnModelPackage
@Stability(Stable)
public static interface CfnModelPackage.ModelPackageContainerDefinitionProperty
extends software.amazon.jsii.JsiiSerializable
Describes the Docker container for the model package.
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 modelInput; ModelPackageContainerDefinitionProperty modelPackageContainerDefinitionProperty = ModelPackageContainerDefinitionProperty.builder() .image("image") // the properties below are optional .containerHostname("containerHostname") .environment(Map.of( "environmentKey", "environment")) .framework("framework") .frameworkVersion("frameworkVersion") .imageDigest("imageDigest") .modelDataSource(ModelDataSourceProperty.builder() .s3DataSource(S3ModelDataSourceProperty.builder() .compressionType("compressionType") .s3DataType("s3DataType") .s3Uri("s3Uri") // the properties below are optional .modelAccessConfig(ModelAccessConfigProperty.builder() .acceptEula(false) .build()) .build()) .build()) .modelDataUrl("modelDataUrl") .modelInput(modelInput) .nearestModelName("nearestModelName") .build();
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Nested Class Summary
Modifier and TypeInterfaceDescriptionstatic final class
A builder forCfnModelPackage.ModelPackageContainerDefinitionProperty
static final class
An implementation forCfnModelPackage.ModelPackageContainerDefinitionProperty
-
Method Summary
Modifier and TypeMethodDescriptionbuilder()
default String
The DNS host name for the Docker container.default Object
The environment variables to set in the Docker container.default String
The machine learning framework of the model package container image.default String
The framework version of the Model Package Container Image.getImage()
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.default String
An MD5 hash of the training algorithm that identifies the Docker image used for training.default Object
Specifies the location of ML model data to deploy during endpoint creation.default String
The Amazon S3 path where the model artifacts, which result from model training, are stored.default Object
A structure with Model Input details.default String
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getImage
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.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]
andregistry/repository[@digest]
image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker . -
getContainerHostname
The DNS host name for the Docker container. -
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. -
getFramework
The machine learning framework of the model package container image. -
getFrameworkVersion
The framework version of the Model Package Container Image. -
getImageDigest
An MD5 hash of the training algorithm that identifies the Docker image used for training. -
getModelDataSource
Specifies the location of ML model data to deploy during endpoint creation. -
getModelDataUrl
The Amazon 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 model artifacts must be in an S3 bucket that is in the same region as the model package.
-
getModelInput
A structure with Model Input details. -
getNearestModelName
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.You can find a list of benchmarked models by calling
ListModelMetadata
. -
builder
-