software.amazon.awssdk.services.sagemaker.model

Class HyperParameterTuningJobWarmStartConfig

java.lang.Object

software.amazon.awssdk.services.sagemaker.model.HyperParameterTuningJobWarmStartConfig

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<HyperParameterTuningJobWarmStartConfig.Builder,HyperParameterTuningJobWarmStartConfig>

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

Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.

All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.

All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	HyperParameterTuningJobWarmStartConfig.Builder

Method Summary

Modifier and Type	Method and Description
static HyperParameterTuningJobWarmStartConfig.Builder	builder()
boolean	equals(Object obj)
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
List<ParentHyperParameterTuningJob>	parentHyperParameterTuningJobs() An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job.
List<SdkField<?>>	sdkFields()
static Class<? extends HyperParameterTuningJobWarmStartConfig.Builder>	serializableBuilderClass()
HyperParameterTuningJobWarmStartConfig.Builder	toBuilder() Take this object and create a builder that contains all of the current property values of this object.
String	toString()
HyperParameterTuningJobWarmStartType	warmStartType() Specifies one of the following:
String	warmStartTypeAsString() Specifies one of the following:

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

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

copy

Method Detail

parentHyperParameterTuningJobs

public List<ParentHyperParameterTuningJob> parentHyperParameterTuningJobs()

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

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

Returns:

An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job. For more information about warm starting a hyperparameter tuning job, see Using a Previous Hyperparameter Tuning Job as a Starting Point.

Hyperparameter tuning jobs created before October 1, 2018 cannot be used as parent jobs for warm start tuning jobs.

warmStartType

public HyperParameterTuningJobWarmStartType warmStartType()

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

If the service returns an enum value that is not available in the current SDK version, warmStartType will return HyperParameterTuningJobWarmStartType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from warmStartTypeAsString().

Returns:

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

See Also:

HyperParameterTuningJobWarmStartType

warmStartTypeAsString

public String warmStartTypeAsString()

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

If the service returns an enum value that is not available in the current SDK version, warmStartType will return HyperParameterTuningJobWarmStartType.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from warmStartTypeAsString().

Returns:

Specifies one of the following:

IDENTICAL_DATA_AND_ALGORITHM

The new hyperparameter tuning job uses the same input data and training image as the parent tuning jobs. You can change the hyperparameter ranges to search and the maximum number of training jobs that the hyperparameter tuning job launches. You cannot use a new version of the training algorithm, unless the changes in the new version do not affect the algorithm itself. For example, changes that improve logging or adding support for a different data format are allowed. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

TRANSFER_LEARNING

The new hyperparameter tuning job can include input data, hyperparameter ranges, maximum number of concurrent training jobs, and maximum number of training jobs that are different than those of its parent hyperparameter tuning jobs. The training image can also be a different version from the version used in the parent hyperparameter tuning job. You can also change hyperparameters from tunable to static, and from static to tunable, but the total number of static plus tunable hyperparameters must remain the same as it is in all parent jobs. The objective metric for the new tuning job must be the same as for all parent jobs.

See Also:

HyperParameterTuningJobWarmStartType

toBuilder

public HyperParameterTuningJobWarmStartConfig.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<HyperParameterTuningJobWarmStartConfig.Builder,HyperParameterTuningJobWarmStartConfig>

Returns:

a builder for type T

builder

public static HyperParameterTuningJobWarmStartConfig.Builder builder()

serializableBuilderClass

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

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

toString

public String toString()

Overrides:

toString in class Object

getValueForField

public <T> Optional<T> getValueForField(String fieldName,
                                        Class<T> clazz)

sdkFields

public 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.