Interface CreateInferenceExperimentRequest.Builder
- All Superinterfaces:
AwsRequest.Builder,Buildable,CopyableBuilder<CreateInferenceExperimentRequest.Builder,,CreateInferenceExperimentRequest> SageMakerRequest.Builder,SdkBuilder<CreateInferenceExperimentRequest.Builder,,CreateInferenceExperimentRequest> SdkPojo,SdkRequest.Builder
- Enclosing class:
CreateInferenceExperimentRequest
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Method Summary
Modifier and TypeMethodDescriptiondataStorageConfig(Consumer<InferenceExperimentDataStorageConfig.Builder> dataStorageConfig) The Amazon S3 location and configuration for storing inference request and response data.dataStorageConfig(InferenceExperimentDataStorageConfig dataStorageConfig) The Amazon S3 location and configuration for storing inference request and response data.description(String description) A description for the inference experiment.endpointName(String endpointName) The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.modelVariants(Collection<ModelVariantConfig> modelVariants) An array ofModelVariantConfigobjects.modelVariants(Consumer<ModelVariantConfig.Builder>... modelVariants) An array ofModelVariantConfigobjects.modelVariants(ModelVariantConfig... modelVariants) An array ofModelVariantConfigobjects.The name for the inference experiment.overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Add an optional request override configuration.overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) Add an optional request override configuration.The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.schedule(Consumer<InferenceExperimentSchedule.Builder> schedule) The duration for which you want the inference experiment to run.schedule(InferenceExperimentSchedule schedule) The duration for which you want the inference experiment to run.shadowModeConfig(Consumer<ShadowModeConfig.Builder> shadowModeConfig) The configuration ofShadowModeinference experiment type.shadowModeConfig(ShadowModeConfig shadowModeConfig) The configuration ofShadowModeinference experiment type.tags(Collection<Tag> tags) Array of key-value pairs.tags(Consumer<Tag.Builder>... tags) Array of key-value pairs.Array of key-value pairs.The type of the inference experiment that you want to run.type(InferenceExperimentType type) The type of the inference experiment that you want to run.Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder
overrideConfigurationMethods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copyMethods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder
buildMethods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, buildMethods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
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Method Details
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name
The name for the inference experiment.
- Parameters:
name- The name for the inference experiment.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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type
The type of the inference experiment that you want to run. The following types of experiments are possible:
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ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
- Parameters:
type- The type of the inference experiment that you want to run. The following types of experiments are possible:-
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
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- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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type
The type of the inference experiment that you want to run. The following types of experiments are possible:
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ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
- Parameters:
type- The type of the inference experiment that you want to run. The following types of experiments are possible:-
ShadowMode: You can use this type to validate a shadow variant. For more information, see Shadow tests.
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- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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schedule
The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
- Parameters:
schedule- The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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schedule
default CreateInferenceExperimentRequest.Builder schedule(Consumer<InferenceExperimentSchedule.Builder> schedule) The duration for which you want the inference experiment to run. If you don't specify this field, the experiment automatically starts immediately upon creation and concludes after 7 days.
This is a convenience method that creates an instance of theInferenceExperimentSchedule.Builderavoiding the need to create one manually viaInferenceExperimentSchedule.builder().When the
Consumercompletes,SdkBuilder.build()is called immediately and its result is passed toschedule(InferenceExperimentSchedule).- Parameters:
schedule- a consumer that will call methods onInferenceExperimentSchedule.Builder- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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description
A description for the inference experiment.
- Parameters:
description- A description for the inference experiment.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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roleArn
The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.
- Parameters:
roleArn- The ARN of the IAM role that Amazon SageMaker can assume to access model artifacts and container images, and manage Amazon SageMaker Inference endpoints for model deployment.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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endpointName
The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.
- Parameters:
endpointName- The name of the Amazon SageMaker endpoint on which you want to run the inference experiment.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelVariants
CreateInferenceExperimentRequest.Builder modelVariants(Collection<ModelVariantConfig> modelVariants) An array of
ModelVariantConfigobjects. There is one for each variant in the inference experiment. EachModelVariantConfigobject in the array describes the infrastructure configuration for the corresponding variant.- Parameters:
modelVariants- An array ofModelVariantConfigobjects. There is one for each variant in the inference experiment. EachModelVariantConfigobject in the array describes the infrastructure configuration for the corresponding variant.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelVariants
An array of
ModelVariantConfigobjects. There is one for each variant in the inference experiment. EachModelVariantConfigobject in the array describes the infrastructure configuration for the corresponding variant.- Parameters:
modelVariants- An array ofModelVariantConfigobjects. There is one for each variant in the inference experiment. EachModelVariantConfigobject in the array describes the infrastructure configuration for the corresponding variant.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelVariants
CreateInferenceExperimentRequest.Builder modelVariants(Consumer<ModelVariantConfig.Builder>... modelVariants) An array of
This is a convenience method that creates an instance of theModelVariantConfigobjects. There is one for each variant in the inference experiment. EachModelVariantConfigobject in the array describes the infrastructure configuration for the corresponding variant.ModelVariantConfig.Builderavoiding the need to create one manually viaModelVariantConfig.builder().When the
Consumercompletes,SdkBuilder.build()is called immediately and its result is passed tomodelVariants(List<ModelVariantConfig>).- Parameters:
modelVariants- a consumer that will call methods onModelVariantConfig.Builder- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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dataStorageConfig
CreateInferenceExperimentRequest.Builder dataStorageConfig(InferenceExperimentDataStorageConfig dataStorageConfig) The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
- Parameters:
dataStorageConfig- The Amazon S3 location and configuration for storing inference request and response data.This is an optional parameter that you can use for data capture. For more information, see Capture data.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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dataStorageConfig
default CreateInferenceExperimentRequest.Builder dataStorageConfig(Consumer<InferenceExperimentDataStorageConfig.Builder> dataStorageConfig) The Amazon S3 location and configuration for storing inference request and response data.
This is an optional parameter that you can use for data capture. For more information, see Capture data.
This is a convenience method that creates an instance of theInferenceExperimentDataStorageConfig.Builderavoiding the need to create one manually viaInferenceExperimentDataStorageConfig.builder().When the
Consumercompletes,SdkBuilder.build()is called immediately and its result is passed todataStorageConfig(InferenceExperimentDataStorageConfig).- Parameters:
dataStorageConfig- a consumer that will call methods onInferenceExperimentDataStorageConfig.Builder- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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shadowModeConfig
The configuration of
ShadowModeinference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.- Parameters:
shadowModeConfig- The configuration ofShadowModeinference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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shadowModeConfig
default CreateInferenceExperimentRequest.Builder shadowModeConfig(Consumer<ShadowModeConfig.Builder> shadowModeConfig) The configuration of
This is a convenience method that creates an instance of theShadowModeinference experiment type. Use this field to specify a production variant which takes all the inference requests, and a shadow variant to which Amazon SageMaker replicates a percentage of the inference requests. For the shadow variant also specify the percentage of requests that Amazon SageMaker replicates.ShadowModeConfig.Builderavoiding the need to create one manually viaShadowModeConfig.builder().When the
Consumercompletes,SdkBuilder.build()is called immediately and its result is passed toshadowModeConfig(ShadowModeConfig).- Parameters:
shadowModeConfig- a consumer that will call methods onShadowModeConfig.Builder- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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kmsKey
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. The
KmsKeycan be any of the following formats:-
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab" -
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" -
KMS key Alias
"alias/ExampleAlias" -
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call
kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys forOutputDataConfig. If you use a bucket policy with ans3:PutObjectpermission that only allows objects with server-side encryption, set the condition key ofs3:x-amz-server-side-encryptionto"aws:kms". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpointandUpdateEndpointrequests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.- Parameters:
kmsKey- The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint. TheKmsKeycan be any of the following formats:-
KMS key ID
"1234abcd-12ab-34cd-56ef-1234567890ab" -
Amazon Resource Name (ARN) of a KMS key
"arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab" -
KMS key Alias
"alias/ExampleAlias" -
Amazon Resource Name (ARN) of a KMS key Alias
"arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias"
If you use a KMS key ID or an alias of your KMS key, the Amazon SageMaker execution role must include permissions to call
kms:Encrypt. If you don't provide a KMS key ID, Amazon SageMaker uses the default KMS key for Amazon S3 for your role's account. Amazon SageMaker uses server-side encryption with KMS managed keys forOutputDataConfig. If you use a bucket policy with ans3:PutObjectpermission that only allows objects with server-side encryption, set the condition key ofs3:x-amz-server-side-encryptionto"aws:kms". For more information, see KMS managed Encryption Keys in the Amazon Simple Storage Service Developer Guide.The KMS key policy must grant permission to the IAM role that you specify in your
CreateEndpointandUpdateEndpointrequests. For more information, see Using Key Policies in Amazon Web Services KMS in the Amazon Web Services Key Management Service Developer Guide.-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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tags
Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
- Parameters:
tags- Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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tags
Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
- Parameters:
tags- Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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tags
Array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging your Amazon Web Services Resources.
This is a convenience method that creates an instance of theTag.Builderavoiding the need to create one manually viaTag.builder().When the
Consumercompletes,SdkBuilder.build()is called immediately and its result is passed totags(List<Tag>).- Parameters:
tags- a consumer that will call methods onTag.Builder- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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overrideConfiguration
CreateInferenceExperimentRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) Description copied from interface:AwsRequest.BuilderAdd an optional request override configuration.- Specified by:
overrideConfigurationin interfaceAwsRequest.Builder- Parameters:
overrideConfiguration- The override configuration.- Returns:
- This object for method chaining.
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overrideConfiguration
CreateInferenceExperimentRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Description copied from interface:AwsRequest.BuilderAdd an optional request override configuration.- Specified by:
overrideConfigurationin interfaceAwsRequest.Builder- Parameters:
builderConsumer- AConsumerto which an emptyAwsRequestOverrideConfiguration.Builderwill be given.- Returns:
- This object for method chaining.
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