Class HyperParameterTuningJobWarmStartConfig

java.lang.Object
software.amazon.awssdk.services.sagemaker.model.HyperParameterTuningJobWarmStartConfig
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:
  • Method Details

    • 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 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.
    • 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.

    • warmStartType

      public final 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:
    • warmStartTypeAsString

      public final 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:
    • 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

    • serializableBuilderClass

      public static Class<? extends HyperParameterTuningJobWarmStartConfig.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)
      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)
    • 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.