/* * Copyright 2018-2023 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); } }