Class CfnModel.ContainerDefinitionProperty.Jsii$Proxy
- All Implemented Interfaces:
CfnModel.ContainerDefinitionProperty,software.amazon.jsii.JsiiSerializable
- Enclosing interface:
- CfnModel.ContainerDefinitionProperty
CfnModel.ContainerDefinitionProperty-
Nested Class Summary
Nested classes/interfaces inherited from class software.amazon.jsii.JsiiObject
software.amazon.jsii.JsiiObject.InitializationModeNested classes/interfaces inherited from interface software.amazon.awscdk.services.sagemaker.CfnModel.ContainerDefinitionProperty
CfnModel.ContainerDefinitionProperty.Builder, CfnModel.ContainerDefinitionProperty.Jsii$Proxy -
Constructor Summary
ConstructorsModifierConstructorDescriptionprotectedConstructor that initializes the object based on literal property values passed by theCfnModel.ContainerDefinitionProperty.Builder.protectedJsii$Proxy(software.amazon.jsii.JsiiObjectRef objRef) Constructor that initializes the object based on values retrieved from the JsiiObject. -
Method Summary
Modifier and TypeMethodDescriptioncom.fasterxml.jackson.databind.JsonNodefinal booleanfinal StringThis parameter is ignored for models that contain only aPrimaryContainer.final ObjectThe environment variables to set in the Docker container.final StringgetImage()The path where inference code is stored.final ObjectSpecifies whether the model container is in Amazon ECR or a private Docker registry accessible from your Amazon Virtual Private Cloud (VPC).final StringThe inference specification name in the model package version.final StringgetMode()Whether the container hosts a single model or multiple models.final StringThe S3 path where the model artifacts, which result from model training, are stored.final StringThe name or Amazon Resource Name (ARN) of the model package to use to create the model.final ObjectSpecifies additional configuration for multi-model endpoints.final inthashCode()Methods inherited from class software.amazon.jsii.JsiiObject
jsiiAsyncCall, jsiiAsyncCall, jsiiCall, jsiiCall, jsiiGet, jsiiGet, jsiiSet, jsiiStaticCall, jsiiStaticCall, jsiiStaticGet, jsiiStaticGet, jsiiStaticSet, jsiiStaticSet
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Constructor Details
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Jsii$Proxy
protected Jsii$Proxy(software.amazon.jsii.JsiiObjectRef objRef) Constructor that initializes the object based on values retrieved from the JsiiObject.- Parameters:
objRef- Reference to the JSII managed object.
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Jsii$Proxy
Constructor that initializes the object based on literal property values passed by theCfnModel.ContainerDefinitionProperty.Builder.
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Method Details
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getContainerHostname
Description copied from interface:CfnModel.ContainerDefinitionPropertyThis parameter is ignored for models that contain only aPrimaryContainer.When a
ContainerDefinitionis 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 aContainerDefinitionthat is part of an inference pipeline, a unique name is automatically assigned based on the position of theContainerDefinitionin the pipeline. If you specify a value for theContainerHostNamefor anyContainerDefinitionthat is part of an inference pipeline, you must specify a value for theContainerHostNameparameter of everyContainerDefinitionin that pipeline.- Specified by:
getContainerHostnamein interfaceCfnModel.ContainerDefinitionProperty
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getEnvironment
Description copied from interface:CfnModel.ContainerDefinitionPropertyThe environment variables to set in the Docker container.Each key and value in the
Environmentstring to string map can have length of up to 1024. We support up to 16 entries in the map.- Specified by:
getEnvironmentin interfaceCfnModel.ContainerDefinitionProperty
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getImage
Description copied from interface:CfnModel.ContainerDefinitionPropertyThe 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]andregistry/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.
- Specified by:
getImagein interfaceCfnModel.ContainerDefinitionProperty
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getImageConfig
Description copied from interface:CfnModel.ContainerDefinitionPropertySpecifies 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.
- Specified by:
getImageConfigin interfaceCfnModel.ContainerDefinitionProperty
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getInferenceSpecificationName
Description copied from interface:CfnModel.ContainerDefinitionPropertyThe inference specification name in the model package version.- Specified by:
getInferenceSpecificationNamein interfaceCfnModel.ContainerDefinitionProperty
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getMode
Description copied from interface:CfnModel.ContainerDefinitionPropertyWhether the container hosts a single model or multiple models.- Specified by:
getModein interfaceCfnModel.ContainerDefinitionProperty
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getModelDataUrl
Description copied from interface:CfnModel.ContainerDefinitionPropertyThe 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.- Specified by:
getModelDataUrlin interfaceCfnModel.ContainerDefinitionProperty
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getModelPackageName
Description copied from interface:CfnModel.ContainerDefinitionPropertyThe name or Amazon Resource Name (ARN) of the model package to use to create the model.- Specified by:
getModelPackageNamein interfaceCfnModel.ContainerDefinitionProperty
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getMultiModelConfig
Description copied from interface:CfnModel.ContainerDefinitionPropertySpecifies additional configuration for multi-model endpoints.- Specified by:
getMultiModelConfigin interfaceCfnModel.ContainerDefinitionProperty
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$jsii$toJson
@Internal public com.fasterxml.jackson.databind.JsonNode $jsii$toJson()- Specified by:
$jsii$toJsonin interfacesoftware.amazon.jsii.JsiiSerializable
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equals
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hashCode
public final int hashCode()
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