com.amazonaws.services.sagemaker.model.HyperParameterTuningJobWarmStartConfig Maven / Gradle / Ivy
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/*
* Copyright 2019-2024 Amazon.com, Inc. or its affiliates. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file except in compliance with
* the License. A copy of the License is located at
*
* http://aws.amazon.com/apache2.0
*
* or in the "license" file accompanying this file. This file is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
* CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions
* and limitations under the License.
*/
package com.amazonaws.services.sagemaker.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;
/**
*
* 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 AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class HyperParameterTuningJobWarmStartConfig implements Serializable, Cloneable, StructuredPojo {
/**
*
* 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.
*
*/
private java.util.List parentHyperParameterTuningJobs;
/**
*
* 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.
*
*
*
*/
private String warmStartType;
/**
*
* 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.
*
*
* @return 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.
*/
public java.util.List getParentHyperParameterTuningJobs() {
return 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.
*
*
* @param 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.
*/
public void setParentHyperParameterTuningJobs(java.util.Collection parentHyperParameterTuningJobs) {
if (parentHyperParameterTuningJobs == null) {
this.parentHyperParameterTuningJobs = null;
return;
}
this.parentHyperParameterTuningJobs = new java.util.ArrayList(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.
*
*
* NOTE: This method appends the values to the existing list (if any). Use
* {@link #setParentHyperParameterTuningJobs(java.util.Collection)} or
* {@link #withParentHyperParameterTuningJobs(java.util.Collection)} if you want to override the existing values.
*
*
* @param 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.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningJobWarmStartConfig withParentHyperParameterTuningJobs(ParentHyperParameterTuningJob... parentHyperParameterTuningJobs) {
if (this.parentHyperParameterTuningJobs == null) {
setParentHyperParameterTuningJobs(new java.util.ArrayList(parentHyperParameterTuningJobs.length));
}
for (ParentHyperParameterTuningJob ele : parentHyperParameterTuningJobs) {
this.parentHyperParameterTuningJobs.add(ele);
}
return this;
}
/**
*
* 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.
*
*
* @param 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.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public HyperParameterTuningJobWarmStartConfig withParentHyperParameterTuningJobs(
java.util.Collection parentHyperParameterTuningJobs) {
setParentHyperParameterTuningJobs(parentHyperParameterTuningJobs);
return this;
}
/**
*
* 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.
*
*
*
*
* @param 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.
*
*
* @see HyperParameterTuningJobWarmStartType
*/
public void setWarmStartType(String warmStartType) {
this.warmStartType = 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.
*
*
*
*
* @return 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 HyperParameterTuningJobWarmStartType
*/
public String getWarmStartType() {
return this.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.
*
*
*
*
* @param 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.
*
*
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningJobWarmStartType
*/
public HyperParameterTuningJobWarmStartConfig withWarmStartType(String warmStartType) {
setWarmStartType(warmStartType);
return this;
}
/**
*
* 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.
*
*
*
*
* @param 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.
*
*
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningJobWarmStartType
*/
public HyperParameterTuningJobWarmStartConfig withWarmStartType(HyperParameterTuningJobWarmStartType warmStartType) {
this.warmStartType = warmStartType.toString();
return this;
}
/**
* 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.
*
* @return A string representation of this object.
*
* @see java.lang.Object#toString()
*/
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("{");
if (getParentHyperParameterTuningJobs() != null)
sb.append("ParentHyperParameterTuningJobs: ").append(getParentHyperParameterTuningJobs()).append(",");
if (getWarmStartType() != null)
sb.append("WarmStartType: ").append(getWarmStartType());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof HyperParameterTuningJobWarmStartConfig == false)
return false;
HyperParameterTuningJobWarmStartConfig other = (HyperParameterTuningJobWarmStartConfig) obj;
if (other.getParentHyperParameterTuningJobs() == null ^ this.getParentHyperParameterTuningJobs() == null)
return false;
if (other.getParentHyperParameterTuningJobs() != null
&& other.getParentHyperParameterTuningJobs().equals(this.getParentHyperParameterTuningJobs()) == false)
return false;
if (other.getWarmStartType() == null ^ this.getWarmStartType() == null)
return false;
if (other.getWarmStartType() != null && other.getWarmStartType().equals(this.getWarmStartType()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getParentHyperParameterTuningJobs() == null) ? 0 : getParentHyperParameterTuningJobs().hashCode());
hashCode = prime * hashCode + ((getWarmStartType() == null) ? 0 : getWarmStartType().hashCode());
return hashCode;
}
@Override
public HyperParameterTuningJobWarmStartConfig clone() {
try {
return (HyperParameterTuningJobWarmStartConfig) super.clone();
} catch (CloneNotSupportedException e) {
throw new IllegalStateException("Got a CloneNotSupportedException from Object.clone() " + "even though we're Cloneable!", e);
}
}
@com.amazonaws.annotation.SdkInternalApi
@Override
public void marshall(ProtocolMarshaller protocolMarshaller) {
com.amazonaws.services.sagemaker.model.transform.HyperParameterTuningJobWarmStartConfigMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}