software.amazon.awssdk.services.sagemaker.model

Interface CreateAutoMlJobV2Request.Builder

All Superinterfaces:

AwsRequest.Builder, Buildable, CopyableBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>, SageMakerRequest.Builder, SdkBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>, SdkPojo, SdkRequest.Builder

Enclosing class:

CreateAutoMlJobV2Request

public static interface CreateAutoMlJobV2Request.Builder
extends SageMakerRequest.Builder, SdkPojo, CopyableBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>

Method Summary

Modifier and Type	Method and Description
CreateAutoMlJobV2Request.Builder	autoMLJobInputDataConfig(AutoMLJobChannel... autoMLJobInputDataConfig) An array of channel objects describing the input data and their location.
CreateAutoMlJobV2Request.Builder	autoMLJobInputDataConfig(Collection<AutoMLJobChannel> autoMLJobInputDataConfig) An array of channel objects describing the input data and their location.
CreateAutoMlJobV2Request.Builder	autoMLJobInputDataConfig(Consumer<AutoMLJobChannel.Builder>... autoMLJobInputDataConfig) An array of channel objects describing the input data and their location.
CreateAutoMlJobV2Request.Builder	autoMLJobName(String autoMLJobName) Identifies an Autopilot job.
CreateAutoMlJobV2Request.Builder	autoMLJobObjective(AutoMLJobObjective autoMLJobObjective) Specifies a metric to minimize or maximize as the objective of a job.
default CreateAutoMlJobV2Request.Builder	autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> autoMLJobObjective) Specifies a metric to minimize or maximize as the objective of a job.
CreateAutoMlJobV2Request.Builder	autoMLProblemTypeConfig(AutoMLProblemTypeConfig autoMLProblemTypeConfig) Defines the configuration settings of one of the supported problem types.
default CreateAutoMlJobV2Request.Builder	autoMLProblemTypeConfig(Consumer<AutoMLProblemTypeConfig.Builder> autoMLProblemTypeConfig) Defines the configuration settings of one of the supported problem types.
CreateAutoMlJobV2Request.Builder	dataSplitConfig(AutoMLDataSplitConfig dataSplitConfig) This structure specifies how to split the data into train and validation datasets.
default CreateAutoMlJobV2Request.Builder	dataSplitConfig(Consumer<AutoMLDataSplitConfig.Builder> dataSplitConfig) This structure specifies how to split the data into train and validation datasets.
default CreateAutoMlJobV2Request.Builder	modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig) Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
CreateAutoMlJobV2Request.Builder	modelDeployConfig(ModelDeployConfig modelDeployConfig) Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.
CreateAutoMlJobV2Request.Builder	outputDataConfig(AutoMLOutputDataConfig outputDataConfig) Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
default CreateAutoMlJobV2Request.Builder	outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig) Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.
CreateAutoMlJobV2Request.Builder	overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)
CreateAutoMlJobV2Request.Builder	overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)
CreateAutoMlJobV2Request.Builder	roleArn(String roleArn) The ARN of the role that is used to access the data.
CreateAutoMlJobV2Request.Builder	securityConfig(AutoMLSecurityConfig securityConfig) The security configuration for traffic encryption or Amazon VPC settings.
default CreateAutoMlJobV2Request.Builder	securityConfig(Consumer<AutoMLSecurityConfig.Builder> securityConfig) The security configuration for traffic encryption or Amazon VPC settings.
CreateAutoMlJobV2Request.Builder	tags(Collection<Tag> tags) An array of key-value pairs.
CreateAutoMlJobV2Request.Builder	tags(Consumer<Tag.Builder>... tags) An array of key-value pairs.
CreateAutoMlJobV2Request.Builder	tags(Tag... tags) An array of key-value pairs.

Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerRequest.Builder

build

Methods inherited from interface software.amazon.awssdk.awscore.AwsRequest.Builder

overrideConfiguration

Methods inherited from interface software.amazon.awssdk.core.SdkPojo

equalsBySdkFields, sdkFields

Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder

copy

Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder

applyMutation, build

Method Detail

autoMLJobName

CreateAutoMlJobV2Request.Builder autoMLJobName(String autoMLJobName)

Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Parameters:

autoMLJobName - Identifies an Autopilot job. The name must be unique to your account and is case insensitive.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobInputDataConfig

CreateAutoMlJobV2Request.Builder autoMLJobInputDataConfig(Collection<AutoMLJobChannel> autoMLJobInputDataConfig)

An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:

• For Tabular problem types: S3Prefix, ManifestFile.

• For ImageClassification: S3Prefix, ManifestFile, AugmentedManifestFile .

• For TextClassification: S3Prefix.

Parameters:

autoMLJobInputDataConfig - An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:

• For Tabular problem types: S3Prefix, ManifestFile.

• For ImageClassification: S3Prefix, ManifestFile, AugmentedManifestFile.

• For TextClassification: S3Prefix.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobInputDataConfig

CreateAutoMlJobV2Request.Builder autoMLJobInputDataConfig(AutoMLJobChannel... autoMLJobInputDataConfig)

An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:

• For Tabular problem types: S3Prefix, ManifestFile.

• For ImageClassification: S3Prefix, ManifestFile, AugmentedManifestFile .

• For TextClassification: S3Prefix.

Parameters:

autoMLJobInputDataConfig - An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:

• For Tabular problem types: S3Prefix, ManifestFile.

• For ImageClassification: S3Prefix, ManifestFile, AugmentedManifestFile.

• For TextClassification: S3Prefix.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobInputDataConfig

CreateAutoMlJobV2Request.Builder autoMLJobInputDataConfig(Consumer<AutoMLJobChannel.Builder>... autoMLJobInputDataConfig)

An array of channel objects describing the input data and their location. Each channel is a named input source. Similar to the InputDataConfig attribute in the CreateAutoMLJob input parameters. The supported formats depend on the problem type:

• For Tabular problem types: S3Prefix, ManifestFile.

• For ImageClassification: S3Prefix, ManifestFile, AugmentedManifestFile .

• For TextClassification: S3Prefix.

This is a convenience method that creates an instance of the AutoMLJobChannel.Builder avoiding the need to create one manually via AutoMLJobChannel.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #autoMLJobInputDataConfig(List).

Parameters:

autoMLJobInputDataConfig - a consumer that will call methods on AutoMLJobChannel.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

#autoMLJobInputDataConfig(java.util.Collection)

outputDataConfig

CreateAutoMlJobV2Request.Builder outputDataConfig(AutoMLOutputDataConfig outputDataConfig)

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.

Parameters:

outputDataConfig - Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.

Returns:

Returns a reference to this object so that method calls can be chained together.

outputDataConfig

default CreateAutoMlJobV2Request.Builder outputDataConfig(Consumer<AutoMLOutputDataConfig.Builder> outputDataConfig)

Provides information about encryption and the Amazon S3 output path needed to store artifacts from an AutoML job.

This is a convenience method that creates an instance of the AutoMLOutputDataConfig.Builder avoiding the need to create one manually via AutoMLOutputDataConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to outputDataConfig(AutoMLOutputDataConfig).

Parameters:

outputDataConfig - a consumer that will call methods on AutoMLOutputDataConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

outputDataConfig(AutoMLOutputDataConfig)

autoMLProblemTypeConfig

CreateAutoMlJobV2Request.Builder autoMLProblemTypeConfig(AutoMLProblemTypeConfig autoMLProblemTypeConfig)

Defines the configuration settings of one of the supported problem types.

Parameters:

autoMLProblemTypeConfig - Defines the configuration settings of one of the supported problem types.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLProblemTypeConfig

default CreateAutoMlJobV2Request.Builder autoMLProblemTypeConfig(Consumer<AutoMLProblemTypeConfig.Builder> autoMLProblemTypeConfig)

Defines the configuration settings of one of the supported problem types.

This is a convenience method that creates an instance of the AutoMLProblemTypeConfig.Builder avoiding the need to create one manually via AutoMLProblemTypeConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to autoMLProblemTypeConfig(AutoMLProblemTypeConfig).

Parameters:

autoMLProblemTypeConfig - a consumer that will call methods on AutoMLProblemTypeConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

autoMLProblemTypeConfig(AutoMLProblemTypeConfig)

roleArn

CreateAutoMlJobV2Request.Builder roleArn(String roleArn)

The ARN of the role that is used to access the data.

Parameters:

roleArn - The ARN of the role that is used to access the data.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobV2Request.Builder tags(Collection<Tag> tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

Parameters:

tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobV2Request.Builder tags(Tag... tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

Parameters:

tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

Returns:

Returns a reference to this object so that method calls can be chained together.

tags

CreateAutoMlJobV2Request.Builder tags(Consumer<Tag.Builder>... tags)

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, such as by purpose, owner, or environment. For more information, see Tagging Amazon Web ServicesResources. Tag keys must be unique per resource.

This is a convenience method that creates an instance of the Tag.Builder avoiding the need to create one manually via Tag.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to #tags(List).

Parameters:

tags - a consumer that will call methods on Tag.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

#tags(java.util.Collection)

securityConfig

CreateAutoMlJobV2Request.Builder securityConfig(AutoMLSecurityConfig securityConfig)

The security configuration for traffic encryption or Amazon VPC settings.

Parameters:

securityConfig - The security configuration for traffic encryption or Amazon VPC settings.

Returns:

Returns a reference to this object so that method calls can be chained together.

securityConfig

default CreateAutoMlJobV2Request.Builder securityConfig(Consumer<AutoMLSecurityConfig.Builder> securityConfig)

The security configuration for traffic encryption or Amazon VPC settings.

This is a convenience method that creates an instance of the AutoMLSecurityConfig.Builder avoiding the need to create one manually via AutoMLSecurityConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to securityConfig(AutoMLSecurityConfig).

Parameters:

securityConfig - a consumer that will call methods on AutoMLSecurityConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

securityConfig(AutoMLSecurityConfig)

autoMLJobObjective

CreateAutoMlJobV2Request.Builder autoMLJobObjective(AutoMLJobObjective autoMLJobObjective)

Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.

For tabular problem types, you must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig ( TabularJobConfig.ProblemType), or none at all.

Parameters:

autoMLJobObjective - Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.

For tabular problem types, you must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig ( TabularJobConfig.ProblemType), or none at all.

Returns:

Returns a reference to this object so that method calls can be chained together.

autoMLJobObjective

default CreateAutoMlJobV2Request.Builder autoMLJobObjective(Consumer<AutoMLJobObjective.Builder> autoMLJobObjective)

Specifies a metric to minimize or maximize as the objective of a job. If not specified, the default objective metric depends on the problem type. For the list of default values per problem type, see AutoMLJobObjective.

For tabular problem types, you must either provide both the AutoMLJobObjective and indicate the type of supervised learning problem in AutoMLProblemTypeConfig ( TabularJobConfig.ProblemType), or none at all.

This is a convenience method that creates an instance of the AutoMLJobObjective.Builder avoiding the need to create one manually via AutoMLJobObjective.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to autoMLJobObjective(AutoMLJobObjective).

Parameters:

autoMLJobObjective - a consumer that will call methods on AutoMLJobObjective.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

autoMLJobObjective(AutoMLJobObjective)

modelDeployConfig

CreateAutoMlJobV2Request.Builder modelDeployConfig(ModelDeployConfig modelDeployConfig)

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Parameters:

modelDeployConfig - Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

Returns:

Returns a reference to this object so that method calls can be chained together.

modelDeployConfig

default CreateAutoMlJobV2Request.Builder modelDeployConfig(Consumer<ModelDeployConfig.Builder> modelDeployConfig)

Specifies how to generate the endpoint name for an automatic one-click Autopilot model deployment.

This is a convenience method that creates an instance of the ModelDeployConfig.Builder avoiding the need to create one manually via ModelDeployConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to modelDeployConfig(ModelDeployConfig).

Parameters:

modelDeployConfig - a consumer that will call methods on ModelDeployConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

modelDeployConfig(ModelDeployConfig)

dataSplitConfig

CreateAutoMlJobV2Request.Builder dataSplitConfig(AutoMLDataSplitConfig dataSplitConfig)

This structure specifies how to split the data into train and validation datasets.

The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.

Parameters:

dataSplitConfig - This structure specifies how to split the data into train and validation datasets.

The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.

Returns:

Returns a reference to this object so that method calls can be chained together.

dataSplitConfig

default CreateAutoMlJobV2Request.Builder dataSplitConfig(Consumer<AutoMLDataSplitConfig.Builder> dataSplitConfig)

This structure specifies how to split the data into train and validation datasets.

The validation and training datasets must contain the same headers. For jobs created by calling CreateAutoMLJob, the validation dataset must be less than 2 GB in size.

This is a convenience method that creates an instance of the AutoMLDataSplitConfig.Builder avoiding the need to create one manually via AutoMLDataSplitConfig.builder().

When the Consumer completes, SdkBuilder.build() is called immediately and its result is passed to dataSplitConfig(AutoMLDataSplitConfig).

Parameters:

dataSplitConfig - a consumer that will call methods on AutoMLDataSplitConfig.Builder

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

dataSplitConfig(AutoMLDataSplitConfig)

overrideConfiguration

CreateAutoMlJobV2Request.Builder overrideConfiguration(AwsRequestOverrideConfiguration overrideConfiguration)

Specified by:

overrideConfiguration in interface AwsRequest.Builder

overrideConfiguration

CreateAutoMlJobV2Request.Builder overrideConfiguration(Consumer<AwsRequestOverrideConfiguration.Builder> builderConsumer)

Specified by:

overrideConfiguration in interface AwsRequest.Builder