Interface CreateModelPackageRequest.Builder
- All Superinterfaces:
AwsRequest.Builder
,Buildable
,CopyableBuilder<CreateModelPackageRequest.Builder,
,CreateModelPackageRequest> SageMakerRequest.Builder
,SdkBuilder<CreateModelPackageRequest.Builder,
,CreateModelPackageRequest> SdkPojo
,SdkRequest.Builder
- Enclosing class:
CreateModelPackageRequest
-
Method Summary
Modifier and TypeMethodDescriptionadditionalInferenceSpecifications
(Collection<AdditionalInferenceSpecificationDefinition> additionalInferenceSpecifications) An array of additional Inference Specification objects.additionalInferenceSpecifications
(Consumer<AdditionalInferenceSpecificationDefinition.Builder>... additionalInferenceSpecifications) An array of additional Inference Specification objects.additionalInferenceSpecifications
(AdditionalInferenceSpecificationDefinition... additionalInferenceSpecifications) An array of additional Inference Specification objects.certifyForMarketplace
(Boolean certifyForMarketplace) Whether to certify the model package for listing on Amazon Web Services Marketplace.clientToken
(String clientToken) A unique token that guarantees that the call to this API is idempotent.customerMetadataProperties
(Map<String, String> customerMetadataProperties) The metadata properties associated with the model package versions.The machine learning domain of your model package and its components.driftCheckBaselines
(Consumer<DriftCheckBaselines.Builder> driftCheckBaselines) Represents the drift check baselines that can be used when the model monitor is set using the model package.driftCheckBaselines
(DriftCheckBaselines driftCheckBaselines) Represents the drift check baselines that can be used when the model monitor is set using the model package.inferenceSpecification
(Consumer<InferenceSpecification.Builder> inferenceSpecification) Specifies details about inference jobs that you can run with models based on this model package, including the following information:inferenceSpecification
(InferenceSpecification inferenceSpecification) Specifies details about inference jobs that you can run with models based on this model package, including the following information:metadataProperties
(Consumer<MetadataProperties.Builder> metadataProperties) Sets the value of the MetadataProperties property for this object.metadataProperties
(MetadataProperties metadataProperties) Sets the value of the MetadataProperties property for this object.modelApprovalStatus
(String modelApprovalStatus) Whether the model is approved for deployment.modelApprovalStatus
(ModelApprovalStatus modelApprovalStatus) Whether the model is approved for deployment.modelMetrics
(Consumer<ModelMetrics.Builder> modelMetrics) A structure that contains model metrics reports.modelMetrics
(ModelMetrics modelMetrics) A structure that contains model metrics reports.modelPackageDescription
(String modelPackageDescription) A description of the model package.modelPackageGroupName
(String modelPackageGroupName) The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.modelPackageName
(String modelPackageName) The name of the model package.overrideConfiguration
(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Add an optional request override configuration.overrideConfiguration
(AwsRequestOverrideConfiguration overrideConfiguration) Add an optional request override configuration.samplePayloadUrl
(String samplePayloadUrl) The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored.skipModelValidation
(String skipModelValidation) Indicates if you want to skip model validation.skipModelValidation
(SkipModelValidation skipModelValidation) Indicates if you want to skip model validation.sourceAlgorithmSpecification
(Consumer<SourceAlgorithmSpecification.Builder> sourceAlgorithmSpecification) Details about the algorithm that was used to create the model package.sourceAlgorithmSpecification
(SourceAlgorithmSpecification sourceAlgorithmSpecification) Details about the algorithm that was used to create the model package.The URI of the source for the model package.tags
(Collection<Tag> tags) A list of key value pairs associated with the model.tags
(Consumer<Tag.Builder>... tags) A list of key value pairs associated with the model.A list of key value pairs associated with the model.The machine learning task your model package accomplishes.validationSpecification
(Consumer<ModelPackageValidationSpecification.Builder> validationSpecification) Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.validationSpecification
(ModelPackageValidationSpecification validationSpecification) Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder
overrideConfiguration
Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder
build
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
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Method Details
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modelPackageName
The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).
This parameter is required for unversioned models. It is not applicable to versioned models.
- Parameters:
modelPackageName
- The name of the model package. The name must have 1 to 63 characters. Valid characters are a-z, A-Z, 0-9, and - (hyphen).This parameter is required for unversioned models. It is not applicable to versioned models.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelPackageGroupName
The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.
This parameter is required for versioned models, and does not apply to unversioned models.
- Parameters:
modelPackageGroupName
- The name or Amazon Resource Name (ARN) of the model package group that this model version belongs to.This parameter is required for versioned models, and does not apply to unversioned models.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelPackageDescription
A description of the model package.
- Parameters:
modelPackageDescription
- A description of the model package.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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inferenceSpecification
CreateModelPackageRequest.Builder inferenceSpecification(InferenceSpecification inferenceSpecification) Specifies details about inference jobs that you can run with models based on this model package, including the following information:
-
The Amazon ECR paths of containers that contain the inference code and model artifacts.
-
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
-
The input and output content formats that the model package supports for inference.
- Parameters:
inferenceSpecification
- Specifies details about inference jobs that you can run with models based on this model package, including the following information:-
The Amazon ECR paths of containers that contain the inference code and model artifacts.
-
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
-
The input and output content formats that the model package supports for inference.
-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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inferenceSpecification
default CreateModelPackageRequest.Builder inferenceSpecification(Consumer<InferenceSpecification.Builder> inferenceSpecification) Specifies details about inference jobs that you can run with models based on this model package, including the following information:
-
The Amazon ECR paths of containers that contain the inference code and model artifacts.
-
The instance types that the model package supports for transform jobs and real-time endpoints used for inference.
-
The input and output content formats that the model package supports for inference.
InferenceSpecification.Builder
avoiding the need to create one manually viaInferenceSpecification.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toinferenceSpecification(InferenceSpecification)
.- Parameters:
inferenceSpecification
- a consumer that will call methods onInferenceSpecification.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
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validationSpecification
CreateModelPackageRequest.Builder validationSpecification(ModelPackageValidationSpecification validationSpecification) Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
- Parameters:
validationSpecification
- Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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validationSpecification
default CreateModelPackageRequest.Builder validationSpecification(Consumer<ModelPackageValidationSpecification.Builder> validationSpecification) Specifies configurations for one or more transform jobs that SageMaker runs to test the model package.
This is a convenience method that creates an instance of theModelPackageValidationSpecification.Builder
avoiding the need to create one manually viaModelPackageValidationSpecification.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tovalidationSpecification(ModelPackageValidationSpecification)
.- Parameters:
validationSpecification
- a consumer that will call methods onModelPackageValidationSpecification.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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sourceAlgorithmSpecification
CreateModelPackageRequest.Builder sourceAlgorithmSpecification(SourceAlgorithmSpecification sourceAlgorithmSpecification) Details about the algorithm that was used to create the model package.
- Parameters:
sourceAlgorithmSpecification
- Details about the algorithm that was used to create the model package.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
sourceAlgorithmSpecification
default CreateModelPackageRequest.Builder sourceAlgorithmSpecification(Consumer<SourceAlgorithmSpecification.Builder> sourceAlgorithmSpecification) Details about the algorithm that was used to create the model package.
This is a convenience method that creates an instance of theSourceAlgorithmSpecification.Builder
avoiding the need to create one manually viaSourceAlgorithmSpecification.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tosourceAlgorithmSpecification(SourceAlgorithmSpecification)
.- Parameters:
sourceAlgorithmSpecification
- a consumer that will call methods onSourceAlgorithmSpecification.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
certifyForMarketplace
Whether to certify the model package for listing on Amazon Web Services Marketplace.
This parameter is optional for unversioned models, and does not apply to versioned models.
- Parameters:
certifyForMarketplace
- Whether to certify the model package for listing on Amazon Web Services Marketplace.This parameter is optional for unversioned models, and does not apply to versioned models.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tags
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply
ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument.- Parameters:
tags
- A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.If you supply
ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tags
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply
ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument.- Parameters:
tags
- A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.If you supply
ModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tags
A list of key value pairs associated with the model. For more information, see Tagging Amazon Web Services resources in the Amazon Web Services General Reference Guide.
If you supply
This is a convenience method that creates an instance of theModelPackageGroupName
, your model package belongs to the model group you specify and uses the tags associated with the model group. In this case, you cannot supply atag
argument.Tag.Builder
avoiding the need to create one manually viaTag.builder()
.When the
Consumer
completes,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:
-
modelApprovalStatus
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to
Approved
to deploy the model.- Parameters:
modelApprovalStatus
- Whether the model is approved for deployment.This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to
Approved
to deploy the model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
modelApprovalStatus
Whether the model is approved for deployment.
This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to
Approved
to deploy the model.- Parameters:
modelApprovalStatus
- Whether the model is approved for deployment.This parameter is optional for versioned models, and does not apply to unversioned models.
For versioned models, the value of this parameter must be set to
Approved
to deploy the model.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
metadataProperties
Sets the value of the MetadataProperties property for this object.- Parameters:
metadataProperties
- The new value for the MetadataProperties property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
metadataProperties
default CreateModelPackageRequest.Builder metadataProperties(Consumer<MetadataProperties.Builder> metadataProperties) Sets the value of the MetadataProperties property for this object. This is a convenience method that creates an instance of theMetadataProperties.Builder
avoiding the need to create one manually viaMetadataProperties.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tometadataProperties(MetadataProperties)
.- Parameters:
metadataProperties
- a consumer that will call methods onMetadataProperties.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
modelMetrics
A structure that contains model metrics reports.
- Parameters:
modelMetrics
- A structure that contains model metrics reports.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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modelMetrics
A structure that contains model metrics reports.
This is a convenience method that creates an instance of theModelMetrics.Builder
avoiding the need to create one manually viaModelMetrics.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tomodelMetrics(ModelMetrics)
.- Parameters:
modelMetrics
- a consumer that will call methods onModelMetrics.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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clientToken
A unique token that guarantees that the call to this API is idempotent.
- Parameters:
clientToken
- A unique token that guarantees that the call to this API is idempotent.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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domain
The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.
- Parameters:
domain
- The machine learning domain of your model package and its components. Common machine learning domains include computer vision and natural language processing.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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task
The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender:
"IMAGE_CLASSIFICATION"
|"OBJECT_DETECTION"
|"TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
|"FILL_MASK"
|"CLASSIFICATION"
|"REGRESSION"
|"OTHER"
.Specify "OTHER" if none of the tasks listed fit your use case.
- Parameters:
task
- The machine learning task your model package accomplishes. Common machine learning tasks include object detection and image classification. The following tasks are supported by Inference Recommender:"IMAGE_CLASSIFICATION"
|"OBJECT_DETECTION"
|"TEXT_GENERATION"
|"IMAGE_SEGMENTATION"
|"FILL_MASK"
|"CLASSIFICATION"
|"REGRESSION"
|"OTHER"
.Specify "OTHER" if none of the tasks listed fit your use case.
- Returns:
- Returns a reference to this object so that method calls can be chained together.
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samplePayloadUrl
The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.
- Parameters:
samplePayloadUrl
- The Amazon Simple Storage Service (Amazon S3) path where the sample payload is stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix). This archive can hold multiple files that are all equally used in the load test. Each file in the archive must satisfy the size constraints of the InvokeEndpoint call.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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customerMetadataProperties
CreateModelPackageRequest.Builder customerMetadataProperties(Map<String, String> customerMetadataProperties) The metadata properties associated with the model package versions.
- Parameters:
customerMetadataProperties
- The metadata properties associated with the model package versions.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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driftCheckBaselines
Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
- Parameters:
driftCheckBaselines
- Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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driftCheckBaselines
default CreateModelPackageRequest.Builder driftCheckBaselines(Consumer<DriftCheckBaselines.Builder> driftCheckBaselines) Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.
This is a convenience method that creates an instance of theDriftCheckBaselines.Builder
avoiding the need to create one manually viaDriftCheckBaselines.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed todriftCheckBaselines(DriftCheckBaselines)
.- Parameters:
driftCheckBaselines
- a consumer that will call methods onDriftCheckBaselines.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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additionalInferenceSpecifications
CreateModelPackageRequest.Builder additionalInferenceSpecifications(Collection<AdditionalInferenceSpecificationDefinition> additionalInferenceSpecifications) An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
- Parameters:
additionalInferenceSpecifications
- An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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additionalInferenceSpecifications
CreateModelPackageRequest.Builder additionalInferenceSpecifications(AdditionalInferenceSpecificationDefinition... additionalInferenceSpecifications) An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
- Parameters:
additionalInferenceSpecifications
- An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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additionalInferenceSpecifications
CreateModelPackageRequest.Builder additionalInferenceSpecifications(Consumer<AdditionalInferenceSpecificationDefinition.Builder>... additionalInferenceSpecifications) An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.
This is a convenience method that creates an instance of theAdditionalInferenceSpecificationDefinition.Builder
avoiding the need to create one manually viaAdditionalInferenceSpecificationDefinition.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toadditionalInferenceSpecifications(List<AdditionalInferenceSpecificationDefinition>)
.- Parameters:
additionalInferenceSpecifications
- a consumer that will call methods onAdditionalInferenceSpecificationDefinition.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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skipModelValidation
Indicates if you want to skip model validation.
- Parameters:
skipModelValidation
- Indicates if you want to skip model validation.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
skipModelValidation
Indicates if you want to skip model validation.
- Parameters:
skipModelValidation
- Indicates if you want to skip model validation.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
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sourceUri
The URI of the source for the model package. If you want to clone a model package, set it to the model package Amazon Resource Name (ARN). If you want to register a model, set it to the model ARN.
- Parameters:
sourceUri
- The URI of the source for the model package. If you want to clone a model package, set it to the model package Amazon Resource Name (ARN). If you want to register a model, set it to the model ARN.- Returns:
- Returns a reference to this object so that method calls can be chained together.
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overrideConfiguration
CreateModelPackageRequest.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
overrideConfiguration
- The override configuration.- Returns:
- This object for method chaining.
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overrideConfiguration
CreateModelPackageRequest.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer) Description copied from interface:AwsRequest.Builder
Add an optional request override configuration.- Specified by:
overrideConfiguration
in interfaceAwsRequest.Builder
- Parameters:
builderConsumer
- AConsumer
to which an emptyAwsRequestOverrideConfiguration.Builder
will be given.- Returns:
- This object for method chaining.
-