Class HyperParameterTuningJobWarmStartConfig
- java.lang.Object
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- software.amazon.awssdk.services.sagemaker.model.HyperParameterTuningJobWarmStartConfig
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- All Implemented Interfaces:
Serializable
,SdkPojo
,ToCopyableBuilder<HyperParameterTuningJobWarmStartConfig.Builder,HyperParameterTuningJobWarmStartConfig>
@Generated("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
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Nested Class Summary
Nested Classes Modifier and Type Class Description static interface
HyperParameterTuningJobWarmStartConfig.Builder
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description static HyperParameterTuningJobWarmStartConfig.Builder
builder()
boolean
equals(Object obj)
boolean
equalsBySdkFields(Object obj)
<T> Optional<T>
getValueForField(String fieldName, Class<T> clazz)
int
hashCode()
boolean
hasParentHyperParameterTuningJobs()
For responses, this returns true if the service returned a value for the ParentHyperParameterTuningJobs property.List<ParentHyperParameterTuningJob>
parentHyperParameterTuningJobs()
An array of hyperparameter tuning jobs that are used as the starting point for the new hyperparameter tuning job.Map<String,SdkField<?>>
sdkFieldNameToField()
List<SdkField<?>>
sdkFields()
static Class<? extends HyperParameterTuningJobWarmStartConfig.Builder>
serializableBuilderClass()
HyperParameterTuningJobWarmStartConfig.Builder
toBuilder()
String
toString()
Returns a string representation of this object.HyperParameterTuningJobWarmStartType
warmStartType()
Specifies one of the following:String
warmStartTypeAsString()
Specifies one of the following:-
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
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Method Detail
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hasParentHyperParameterTuningJobs
public final boolean hasParentHyperParameterTuningJobs()
For responses, this returns true if the service returned a value for the ParentHyperParameterTuningJobs property. This DOES NOT check that the value is non-empty (for which, you should check theisEmpty()
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.
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parentHyperParameterTuningJobs
public final 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.
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
hasParentHyperParameterTuningJobs()
method.- 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.
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warmStartType
public final HyperParameterTuningJobWarmStartType warmStartType()
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
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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
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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 returnHyperParameterTuningJobWarmStartType.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromwarmStartTypeAsString()
.- Returns:
- Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
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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
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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
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warmStartTypeAsString
public final String warmStartTypeAsString()
Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
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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 returnHyperParameterTuningJobWarmStartType.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromwarmStartTypeAsString()
.- Returns:
- Specifies one of the following:
- IDENTICAL_DATA_AND_ALGORITHM
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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
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toBuilder
public HyperParameterTuningJobWarmStartConfig.Builder toBuilder()
- Specified by:
toBuilder
in interfaceToCopyableBuilder<HyperParameterTuningJobWarmStartConfig.Builder,HyperParameterTuningJobWarmStartConfig>
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builder
public static HyperParameterTuningJobWarmStartConfig.Builder builder()
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serializableBuilderClass
public static Class<? extends HyperParameterTuningJobWarmStartConfig.Builder> serializableBuilderClass()
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equalsBySdkFields
public final boolean equalsBySdkFields(Object obj)
- Specified by:
equalsBySdkFields
in interfaceSdkPojo
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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.
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sdkFieldNameToField
public final Map<String,SdkField<?>> sdkFieldNameToField()
- Specified by:
sdkFieldNameToField
in interfaceSdkPojo
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