Interface ModelPackageContainerDefinition.Builder
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- All Superinterfaces:
Buildable
,CopyableBuilder<ModelPackageContainerDefinition.Builder,ModelPackageContainerDefinition>
,SdkBuilder<ModelPackageContainerDefinition.Builder,ModelPackageContainerDefinition>
,SdkPojo
- Enclosing class:
- ModelPackageContainerDefinition
public static interface ModelPackageContainerDefinition.Builder extends SdkPojo, CopyableBuilder<ModelPackageContainerDefinition.Builder,ModelPackageContainerDefinition>
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Method Summary
All Methods Instance Methods Abstract Methods Default Methods Modifier and Type Method Description default ModelPackageContainerDefinition.Builder
additionalS3DataSource(Consumer<AdditionalS3DataSource.Builder> additionalS3DataSource)
The additional data source that is used during inference in the Docker container for your model package.ModelPackageContainerDefinition.Builder
additionalS3DataSource(AdditionalS3DataSource additionalS3DataSource)
The additional data source that is used during inference in the Docker container for your model package.ModelPackageContainerDefinition.Builder
containerHostname(String containerHostname)
The DNS host name for the Docker container.ModelPackageContainerDefinition.Builder
environment(Map<String,String> environment)
The environment variables to set in the Docker container.ModelPackageContainerDefinition.Builder
framework(String framework)
The machine learning framework of the model package container image.ModelPackageContainerDefinition.Builder
frameworkVersion(String frameworkVersion)
The framework version of the Model Package Container Image.ModelPackageContainerDefinition.Builder
image(String image)
The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.ModelPackageContainerDefinition.Builder
imageDigest(String imageDigest)
An MD5 hash of the training algorithm that identifies the Docker image used for training.default ModelPackageContainerDefinition.Builder
modelDataSource(Consumer<ModelDataSource.Builder> modelDataSource)
Specifies the location of ML model data to deploy during endpoint creation.ModelPackageContainerDefinition.Builder
modelDataSource(ModelDataSource modelDataSource)
Specifies the location of ML model data to deploy during endpoint creation.ModelPackageContainerDefinition.Builder
modelDataUrl(String modelDataUrl)
The Amazon S3 path where the model artifacts, which result from model training, are stored.default ModelPackageContainerDefinition.Builder
modelInput(Consumer<ModelInput.Builder> modelInput)
A structure with Model Input details.ModelPackageContainerDefinition.Builder
modelInput(ModelInput modelInput)
A structure with Model Input details.ModelPackageContainerDefinition.Builder
nearestModelName(String nearestModelName)
The name of a pre-trained machine learning benchmarked by Amazon SageMaker Inference Recommender model that matches your model.ModelPackageContainerDefinition.Builder
productId(String productId)
The Amazon Web Services Marketplace product ID of the model package.-
Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
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Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
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Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFieldNameToField, sdkFields
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Method Detail
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containerHostname
ModelPackageContainerDefinition.Builder containerHostname(String containerHostname)
The DNS host name for the Docker container.
- Parameters:
containerHostname
- The DNS host name for the Docker container.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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image
ModelPackageContainerDefinition.Builder image(String image)
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.- Parameters:
image
- 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.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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imageDigest
ModelPackageContainerDefinition.Builder imageDigest(String imageDigest)
An MD5 hash of the training algorithm that identifies the Docker image used for training.
- Parameters:
imageDigest
- An MD5 hash of the training algorithm that identifies the Docker image used for training.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelDataUrl
ModelPackageContainerDefinition.Builder modelDataUrl(String modelDataUrl)
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.
- Parameters:
modelDataUrl
- The Amazon S3 path where the model artifacts, which result from model training, are stored. This path must point to a singlegzip
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.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelDataSource
ModelPackageContainerDefinition.Builder modelDataSource(ModelDataSource modelDataSource)
Specifies the location of ML model data to deploy during endpoint creation.
- Parameters:
modelDataSource
- Specifies the location of ML model data to deploy during endpoint creation.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelDataSource
default ModelPackageContainerDefinition.Builder modelDataSource(Consumer<ModelDataSource.Builder> modelDataSource)
Specifies the location of ML model data to deploy during endpoint creation.
This is a convenience method that creates an instance of theModelDataSource.Builder
avoiding the need to create one manually viaModelDataSource.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tomodelDataSource(ModelDataSource)
.- Parameters:
modelDataSource
- a consumer that will call methods onModelDataSource.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
modelDataSource(ModelDataSource)
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productId
ModelPackageContainerDefinition.Builder productId(String productId)
The Amazon Web Services Marketplace product ID of the model package.
- Parameters:
productId
- The Amazon Web Services Marketplace product ID of the model package.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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environment
ModelPackageContainerDefinition.Builder environment(Map<String,String> 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.- Parameters:
environment
- The environment variables to set in the Docker container. Each key and value in theEnvironment
string to string map can have length of up to 1024. We support up to 16 entries in the map.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelInput
ModelPackageContainerDefinition.Builder modelInput(ModelInput modelInput)
A structure with Model Input details.
- Parameters:
modelInput
- A structure with Model Input details.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelInput
default ModelPackageContainerDefinition.Builder modelInput(Consumer<ModelInput.Builder> modelInput)
A structure with Model Input details.
This is a convenience method that creates an instance of theModelInput.Builder
avoiding the need to create one manually viaModelInput.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tomodelInput(ModelInput)
.- Parameters:
modelInput
- a consumer that will call methods onModelInput.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
modelInput(ModelInput)
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framework
ModelPackageContainerDefinition.Builder framework(String framework)
The machine learning framework of the model package container image.
- Parameters:
framework
- The machine learning framework of the model package container image.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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frameworkVersion
ModelPackageContainerDefinition.Builder frameworkVersion(String frameworkVersion)
The framework version of the Model Package Container Image.
- Parameters:
frameworkVersion
- The framework version of the Model Package Container Image.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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nearestModelName
ModelPackageContainerDefinition.Builder nearestModelName(String nearestModelName)
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
.- Parameters:
nearestModelName
- 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 callingListModelMetadata
.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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additionalS3DataSource
ModelPackageContainerDefinition.Builder additionalS3DataSource(AdditionalS3DataSource additionalS3DataSource)
The additional data source that is used during inference in the Docker container for your model package.
- Parameters:
additionalS3DataSource
- The additional data source that is used during inference in the Docker container for your model package.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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additionalS3DataSource
default ModelPackageContainerDefinition.Builder additionalS3DataSource(Consumer<AdditionalS3DataSource.Builder> additionalS3DataSource)
The additional data source that is used during inference in the Docker container for your model package.
This is a convenience method that creates an instance of theAdditionalS3DataSource.Builder
avoiding the need to create one manually viaAdditionalS3DataSource.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toadditionalS3DataSource(AdditionalS3DataSource)
.- Parameters:
additionalS3DataSource
- a consumer that will call methods onAdditionalS3DataSource.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
additionalS3DataSource(AdditionalS3DataSource)
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