Class CreateAutoMlJobV2Request

java.lang.Object
software.amazon.awssdk.core.SdkRequest
software.amazon.awssdk.awscore.AwsRequest
software.amazon.awssdk.services.sagemaker.model.SageMakerRequest
software.amazon.awssdk.services.sagemaker.model.CreateAutoMlJobV2Request
All Implemented Interfaces:
SdkPojo, ToCopyableBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>
@Generated("software.amazon.awssdk:codegen") public final class CreateAutoMlJobV2Request extends SageMakerRequest implements ToCopyableBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>

  • Method Details

    • autoMLJobName

      public final String autoMLJobName()

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

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

    • hasAutoMLJobInputDataConfig

      public final boolean hasAutoMLJobInputDataConfig()
      For responses, this returns true if the service returned a value for the AutoMLJobInputDataConfig property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

    • autoMLJobInputDataConfig

      public final List<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 image classification: S3Prefix, ManifestFile, AugmentedManifestFile.

      • For text classification: S3Prefix.

      • For time-series forecasting: S3Prefix.

      • For text generation (LLMs fine-tuning): S3Prefix.

      Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

      This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasAutoMLJobInputDataConfig() method.

      Returns:
      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 image classification: S3Prefix, ManifestFile, AugmentedManifestFile.

      • For text classification: S3Prefix.

      • For time-series forecasting: S3Prefix.

      • For text generation (LLMs fine-tuning): S3Prefix.

    • outputDataConfig

      public final AutoMLOutputDataConfig outputDataConfig()

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

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

    • autoMLProblemTypeConfig

      public final AutoMLProblemTypeConfig autoMLProblemTypeConfig()

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

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

    • roleArn

      public final String roleArn()

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

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

    • hasTags

      public final boolean hasTags()
      For responses, this returns true if the service returned a value for the Tags property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

    • tags

      public final List<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.

      Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

      This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasTags() method.

      Returns:
      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.

    • securityConfig

      public final AutoMLSecurityConfig securityConfig()

      The security configuration for traffic encryption or Amazon VPC settings.

      Returns:
      The security configuration for traffic encryption or Amazon VPC settings.

    • autoMLJobObjective

      public final 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.

      • For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.

      Returns:
      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.

      • For text generation problem types (LLMs fine-tuning): Fine-tuning language models in Autopilot does not require setting the AutoMLJobObjective field. Autopilot fine-tunes LLMs without requiring multiple candidates to be trained and evaluated. Instead, using your dataset, Autopilot directly fine-tunes your target model to enhance a default objective metric, the cross-entropy loss. After fine-tuning a language model, you can evaluate the quality of its generated text using different metrics. For a list of the available metrics, see Metrics for fine-tuning LLMs in Autopilot.

    • modelDeployConfig

      public final ModelDeployConfig modelDeployConfig()

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

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

    • dataSplitConfig

      public final 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.

      This attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.

      Returns:
      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 attribute must not be set for the time-series forecasting problem type, as Autopilot automatically splits the input dataset into training and validation sets.

    • autoMLComputeConfig

      public final AutoMLComputeConfig autoMLComputeConfig()

      Specifies the compute configuration for the AutoML job V2.

      Returns:
      Specifies the compute configuration for the AutoML job V2.

    • toBuilder

      public CreateAutoMlJobV2Request.Builder toBuilder()
      Description copied from interface: ToCopyableBuilder
      Take this object and create a builder that contains all of the current property values of this object.
      Specified by:
      toBuilder in interface ToCopyableBuilder<CreateAutoMlJobV2Request.Builder,CreateAutoMlJobV2Request>
      Specified by:
      toBuilder in class SageMakerRequest
      Returns:
      a builder for type T

    • builder

      public static CreateAutoMlJobV2Request.Builder builder()

    • serializableBuilderClass

      public static Class<? extends CreateAutoMlJobV2Request.Builder> serializableBuilderClass()

    • hashCode

      public final int hashCode()
      Overrides:
      hashCode in class AwsRequest

    • equals

      public final boolean equals(Object obj)
      Overrides:
      equals in class AwsRequest

    • equalsBySdkFields

      public final boolean equalsBySdkFields(Object obj)
      Description copied from interface: SdkPojo
      Indicates whether some other object is "equal to" this one by SDK fields. An SDK field is a modeled, non-inherited field in an SdkPojo class, and is generated based on a service model.

      If an SdkPojo class does not have any inherited fields, equalsBySdkFields and equals are essentially the same.

      Specified by:
      equalsBySdkFields in interface SdkPojo
      Parameters:
      obj - the object to be compared with
      Returns:
      true if the other object equals to this object by sdk fields, false otherwise.

    • toString

      public final String toString()
      Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
      Overrides:
      toString in class Object

    • getValueForField

      public final <T> Optional<T> getValueForField(String fieldName, Class<T> clazz)
      Description copied from class: SdkRequest
      Used to retrieve the value of a field from any class that extends SdkRequest. The field name specified should match the member name from the corresponding service-2.json model specified in the codegen-resources folder for a given service. The class specifies what class to cast the returned value to. If the returned value is also a modeled class, the SdkRequest.getValueForField(String, Class) method will again be available.
      Overrides:
      getValueForField in class SdkRequest
      Parameters:
      fieldName - The name of the member to be retrieved.
      clazz - The class to cast the returned object to.
      Returns:
      Optional containing the casted return value

    • sdkFields

      public final List<SdkField<?>> sdkFields()
      Specified by:
      sdkFields in interface SdkPojo
      Returns:
      List of SdkField in this POJO. May be empty list but should never be null.

    • sdkFieldNameToField

      public final Map<String,SdkField<?>> sdkFieldNameToField()
      Specified by:
      sdkFieldNameToField in interface SdkPojo
      Returns:
      The mapping between the field name and its corresponding field.