HyperParameterTrainingJobDefinition (AWS Java SDK :: Services

java.lang.Object
- software.amazon.awssdk.services.sagemaker.model.HyperParameterTrainingJobDefinition

All Implemented Interfaces:: Serializable, SdkPojo, ToCopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>

@Generated(value="software.amazon.awssdk:codegen")
public final class HyperParameterTrainingJobDefinition
extends Object
implements SdkPojo, Serializable, ToCopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>

Defines the training jobs launched by a hyperparameter tuning job.

See Also:: Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static interface HyperParameterTrainingJobDefinition.Builder

Nested Classes
Modifier and Type	Class and Description
`static interface`	`HyperParameterTrainingJobDefinition.Builder`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`HyperParameterAlgorithmSpecification`	`algorithmSpecification()` The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
`static HyperParameterTrainingJobDefinition.Builder`	`builder()`
`CheckpointConfig`	`checkpointConfig()` Returns the value of the CheckpointConfig property for this object.
`String`	`definitionName()` The job definition name.
`Boolean`	`enableInterContainerTrafficEncryption()` To encrypt all communications between ML compute instances in distributed training, choose `True`.
`Boolean`	`enableManagedSpotTraining()` A Boolean indicating whether managed spot training is enabled (`True`) or not (`False`).
`Boolean`	`enableNetworkIsolation()` Isolates the training container.
`boolean`	`equals(Object obj)`
`boolean`	`equalsBySdkFields(Object obj)`
`<T> Optional<T>`	`getValueForField(String fieldName, Class<T> clazz)`
`int`	`hashCode()`
`boolean`	`hasInputDataConfig()` For responses, this returns true if the service returned a value for the InputDataConfig property.
`boolean`	`hasStaticHyperParameters()` For responses, this returns true if the service returned a value for the StaticHyperParameters property.
`ParameterRanges`	`hyperParameterRanges()` Returns the value of the HyperParameterRanges property for this object.
`HyperParameterTuningResourceConfig`	`hyperParameterTuningResourceConfig()` The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job.
`List<Channel>`	`inputDataConfig()` An array of Channel objects that specify the input for the training jobs that the tuning job launches.
`OutputDataConfig`	`outputDataConfig()` Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
`ResourceConfig`	`resourceConfig()` The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
`RetryStrategy`	`retryStrategy()` The number of times to retry the job when the job fails due to an `InternalServerError`.
`String`	`roleArn()` The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
`List<SdkField<?>>`	`sdkFields()`
`static Class<? extends HyperParameterTrainingJobDefinition.Builder>`	`serializableBuilderClass()`
`Map<String,String>`	`staticHyperParameters()` Specifies the values of hyperparameters that do not change for the tuning job.
`StoppingCondition`	`stoppingCondition()` Specifies a limit to how long a model hyperparameter training job can run.
`HyperParameterTrainingJobDefinition.Builder`	`toBuilder()`
`String`	`toString()` Returns a string representation of this object.
`HyperParameterTuningJobObjective`	`tuningObjective()` Returns the value of the TuningObjective property for this object.
`VpcConfig`	`vpcConfig()` The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to.

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy

- Method Detail
  - definitionName
```
public final String definitionName()
```
    The job definition name.
    
    Returns:
    
    The job definition name.
  - tuningObjective
```
public final HyperParameterTuningJobObjective tuningObjective()
```
    Returns the value of the TuningObjective property for this object.
    
    Returns:
    
    The value of the TuningObjective property for this object.
  - hyperParameterRanges
```
public final ParameterRanges hyperParameterRanges()
```
    Returns the value of the HyperParameterRanges property for this object.
    
    Returns:
    
    The value of the HyperParameterRanges property for this object.
  - hasStaticHyperParameters
```
public final boolean hasStaticHyperParameters()
```
    For responses, this returns true if the service returned a value for the StaticHyperParameters 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.
  - staticHyperParameters
```
public final Map<String,String> staticHyperParameters()
```
    Specifies the values of hyperparameters that do not change for the tuning job.
    
    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 hasStaticHyperParameters() method.
    
    Returns:
    
    Specifies the values of hyperparameters that do not change for the tuning job.
  - algorithmSpecification
```
public final HyperParameterAlgorithmSpecification algorithmSpecification()
```
    The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
    
    Returns:
    
    The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
  - roleArn
```
public final String roleArn()
```
    The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
  - hasInputDataConfig
```
public final boolean hasInputDataConfig()
```
    For responses, this returns true if the service returned a value for the InputDataConfig 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.
  - inputDataConfig
```
public final List<Channel> inputDataConfig()
```
    An array of Channel objects that specify the input for the training jobs that the tuning job launches.
    
    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 hasInputDataConfig() method.
    
    Returns:
    
    An array of Channel objects that specify the input for the training jobs that the tuning job launches.
  - vpcConfig
```
public final VpcConfig vpcConfig()
```
    The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
    
    Returns:
    
    The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
  - outputDataConfig
```
public final OutputDataConfig outputDataConfig()
```
    Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
    
    Returns:
    
    Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
  - resourceConfig
```
public final ResourceConfig resourceConfig()
```
    The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
    
    Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
    
    If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
    
    Returns:
    
    The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
    
    Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes for scratch space. If you want SageMaker to use the storage volume to store the training data, choose File as the TrainingInputMode in the algorithm specification. For distributed training algorithms, specify an instance count greater than 1.
    
    If you want to use hyperparameter optimization with instance type flexibility, use HyperParameterTuningResourceConfig instead.
  - stoppingCondition
```
public final StoppingCondition stoppingCondition()
```
    Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
    
    Returns:
    
    Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long a managed spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
  - enableNetworkIsolation
```
public final Boolean enableNetworkIsolation()
```
    Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
    
    Returns:
    
    Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
  - enableInterContainerTrafficEncryption
```
public final Boolean enableInterContainerTrafficEncryption()
```
    To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
    
    Returns:
    
    To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithm in distributed training.
  - enableManagedSpotTraining
```
public final Boolean enableManagedSpotTraining()
```
    A Boolean indicating whether managed spot training is enabled (True) or not (False).
    
    Returns:
    
    A Boolean indicating whether managed spot training is enabled (True) or not ( False).
  - checkpointConfig
```
public final CheckpointConfig checkpointConfig()
```
    Returns the value of the CheckpointConfig property for this object.
    
    Returns:
    
    The value of the CheckpointConfig property for this object.
  - retryStrategy
```
public final RetryStrategy retryStrategy()
```
    The number of times to retry the job when the job fails due to an InternalServerError.
    
    Returns:
    
    The number of times to retry the job when the job fails due to an InternalServerError.
  - hyperParameterTuningResourceConfig
```
public final HyperParameterTuningResourceConfig hyperParameterTuningResourceConfig()
```
    The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
    
    Returns:
    
    The configuration for the hyperparameter tuning resources, including the compute instances and storage volumes, used for training jobs launched by the tuning job. By default, storage volumes hold model artifacts and incremental states. Choose File for TrainingInputMode in the AlgorithmSpecification parameter to additionally store training data in the storage volume (optional).
  - toBuilder
```
public HyperParameterTrainingJobDefinition.Builder toBuilder()
```
    Specified by:
    
    toBuilder in interface ToCopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>
  - builder
```
public static HyperParameterTrainingJobDefinition.Builder builder()
```
  - serializableBuilderClass
```
public static Class<? extends HyperParameterTrainingJobDefinition.Builder> serializableBuilderClass()
```
  - hashCode
```
public final int hashCode()
```
    Overrides:
    
    hashCode in class Object
  - equals
```
public final boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - equalsBySdkFields
```
public final boolean equalsBySdkFields(Object obj)
```
    Specified by:
    
    equalsBySdkFields in interface SdkPojo
  - 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)
```
  - sdkFields
```
public final List<SdkField<?>> sdkFields()
```
    Specified by:
    
    sdkFields in interface SdkPojo

Class HyperParameterTrainingJobDefinition

Nested Class Summary

Method Summary

Methods inherited from class java.lang.Object

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

Method Detail

definitionName

tuningObjective

hyperParameterRanges

hasStaticHyperParameters

staticHyperParameters

algorithmSpecification

roleArn

hasInputDataConfig

inputDataConfig

vpcConfig

outputDataConfig

resourceConfig

stoppingCondition

enableNetworkIsolation

enableInterContainerTrafficEncryption

enableManagedSpotTraining

checkpointConfig

retryStrategy

hyperParameterTuningResourceConfig

toBuilder

builder

serializableBuilderClass

hashCode

equals

equalsBySdkFields

toString

getValueForField

sdkFields