* An object that provides information about a specific version of a Solution in a Custom dataset group. *
* * @see AWS API * Documentation */ @Generated("com.amazonaws:aws-java-sdk-code-generator") public class SolutionVersion implements Serializable, Cloneable, StructuredPojo { /** ** The name of the solution version. *
*/ private String name; /** ** The ARN of the solution version. *
*/ private String solutionVersionArn; /** ** The ARN of the solution. *
*/ private String solutionArn; /** *
* Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*
* When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
* false (the default), Amazon Personalize uses recipeArn.
*
* The ARN of the recipe used in the solution. *
*/ private String recipeArn; /** ** The event type (for example, 'click' or 'like') that is used for training the model. *
*/ private String eventType; /** ** The Amazon Resource Name (ARN) of the dataset group providing the training data. *
*/ private String datasetGroupArn; /** ** Describes the configuration properties for the solution. *
*/ private SolutionConfig solutionConfig; /** ** The time used to train the model. You are billed for the time it takes to train a model. This field is visible * only after Amazon Personalize successfully trains a model. *
*/ private Double trainingHours; /** *
* The scope of training to be performed when creating the solution version. The FULL option trains the
* solution version based on the entirety of the input solution's training data, while the UPDATE
* option processes only the data that has changed in comparison to the input solution. Choose UPDATE
* when you want to incrementally update your solution version instead of creating an entirely new one.
*
* The UPDATE option can only be used when you already have an active solution version created from the
* input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart
* recipe.
*
* If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model. *
*/ private TunedHPOParams tunedHPOParams; /** ** The status of the solution version. *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** If training a solution version fails, the reason for the failure. *
*/ private String failureReason; /** ** The date and time (in Unix time) that this version of the solution was created. *
*/ private java.util.Date creationDateTime; /** ** The date and time (in Unix time) that the solution was last updated. *
*/ private java.util.Date lastUpdatedDateTime; /** ** The name of the solution version. *
* * @param name * The name of the solution version. */ public void setName(String name) { this.name = name; } /** ** The name of the solution version. *
* * @return The name of the solution version. */ public String getName() { return this.name; } /** ** The name of the solution version. *
* * @param name * The name of the solution version. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withName(String name) { setName(name); return this; } /** ** The ARN of the solution version. *
* * @param solutionVersionArn * The ARN of the solution version. */ public void setSolutionVersionArn(String solutionVersionArn) { this.solutionVersionArn = solutionVersionArn; } /** ** The ARN of the solution version. *
* * @return The ARN of the solution version. */ public String getSolutionVersionArn() { return this.solutionVersionArn; } /** ** The ARN of the solution version. *
* * @param solutionVersionArn * The ARN of the solution version. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withSolutionVersionArn(String solutionVersionArn) { setSolutionVersionArn(solutionVersionArn); return this; } /** ** The ARN of the solution. *
* * @param solutionArn * The ARN of the solution. */ public void setSolutionArn(String solutionArn) { this.solutionArn = solutionArn; } /** ** The ARN of the solution. *
* * @return The ARN of the solution. */ public String getSolutionArn() { return this.solutionArn; } /** ** The ARN of the solution. *
* * @param solutionArn * The ARN of the solution. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withSolutionArn(String solutionArn) { setSolutionArn(solutionArn); return this; } /** *
* Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*
false.
*/
public void setPerformHPO(Boolean performHPO) {
this.performHPO = performHPO;
}
/**
*
* Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*
false.
*/
public Boolean getPerformHPO() {
return this.performHPO;
}
/**
*
* Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*
false.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public SolutionVersion withPerformHPO(Boolean performHPO) {
setPerformHPO(performHPO);
return this;
}
/**
*
* Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*
false.
*/
public Boolean isPerformHPO() {
return this.performHPO;
}
/**
*
* When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
* false (the default), Amazon Personalize uses recipeArn.
*
recipeArn.
*/
public void setPerformAutoML(Boolean performAutoML) {
this.performAutoML = performAutoML;
}
/**
*
* When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
* false (the default), Amazon Personalize uses recipeArn.
*
recipeArn.
*/
public Boolean getPerformAutoML() {
return this.performAutoML;
}
/**
*
* When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
* false (the default), Amazon Personalize uses recipeArn.
*
recipeArn.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public SolutionVersion withPerformAutoML(Boolean performAutoML) {
setPerformAutoML(performAutoML);
return this;
}
/**
*
* When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When
* false (the default), Amazon Personalize uses recipeArn.
*
recipeArn.
*/
public Boolean isPerformAutoML() {
return this.performAutoML;
}
/**
* * The ARN of the recipe used in the solution. *
* * @param recipeArn * The ARN of the recipe used in the solution. */ public void setRecipeArn(String recipeArn) { this.recipeArn = recipeArn; } /** ** The ARN of the recipe used in the solution. *
* * @return The ARN of the recipe used in the solution. */ public String getRecipeArn() { return this.recipeArn; } /** ** The ARN of the recipe used in the solution. *
* * @param recipeArn * The ARN of the recipe used in the solution. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withRecipeArn(String recipeArn) { setRecipeArn(recipeArn); return this; } /** ** The event type (for example, 'click' or 'like') that is used for training the model. *
* * @param eventType * The event type (for example, 'click' or 'like') that is used for training the model. */ public void setEventType(String eventType) { this.eventType = eventType; } /** ** The event type (for example, 'click' or 'like') that is used for training the model. *
* * @return The event type (for example, 'click' or 'like') that is used for training the model. */ public String getEventType() { return this.eventType; } /** ** The event type (for example, 'click' or 'like') that is used for training the model. *
* * @param eventType * The event type (for example, 'click' or 'like') that is used for training the model. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withEventType(String eventType) { setEventType(eventType); return this; } /** ** The Amazon Resource Name (ARN) of the dataset group providing the training data. *
* * @param datasetGroupArn * The Amazon Resource Name (ARN) of the dataset group providing the training data. */ public void setDatasetGroupArn(String datasetGroupArn) { this.datasetGroupArn = datasetGroupArn; } /** ** The Amazon Resource Name (ARN) of the dataset group providing the training data. *
* * @return The Amazon Resource Name (ARN) of the dataset group providing the training data. */ public String getDatasetGroupArn() { return this.datasetGroupArn; } /** ** The Amazon Resource Name (ARN) of the dataset group providing the training data. *
* * @param datasetGroupArn * The Amazon Resource Name (ARN) of the dataset group providing the training data. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withDatasetGroupArn(String datasetGroupArn) { setDatasetGroupArn(datasetGroupArn); return this; } /** ** Describes the configuration properties for the solution. *
* * @param solutionConfig * Describes the configuration properties for the solution. */ public void setSolutionConfig(SolutionConfig solutionConfig) { this.solutionConfig = solutionConfig; } /** ** Describes the configuration properties for the solution. *
* * @return Describes the configuration properties for the solution. */ public SolutionConfig getSolutionConfig() { return this.solutionConfig; } /** ** Describes the configuration properties for the solution. *
* * @param solutionConfig * Describes the configuration properties for the solution. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withSolutionConfig(SolutionConfig solutionConfig) { setSolutionConfig(solutionConfig); return this; } /** ** The time used to train the model. You are billed for the time it takes to train a model. This field is visible * only after Amazon Personalize successfully trains a model. *
* * @param trainingHours * The time used to train the model. You are billed for the time it takes to train a model. This field is * visible only after Amazon Personalize successfully trains a model. */ public void setTrainingHours(Double trainingHours) { this.trainingHours = trainingHours; } /** ** The time used to train the model. You are billed for the time it takes to train a model. This field is visible * only after Amazon Personalize successfully trains a model. *
* * @return The time used to train the model. You are billed for the time it takes to train a model. This field is * visible only after Amazon Personalize successfully trains a model. */ public Double getTrainingHours() { return this.trainingHours; } /** ** The time used to train the model. You are billed for the time it takes to train a model. This field is visible * only after Amazon Personalize successfully trains a model. *
* * @param trainingHours * The time used to train the model. You are billed for the time it takes to train a model. This field is * visible only after Amazon Personalize successfully trains a model. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withTrainingHours(Double trainingHours) { setTrainingHours(trainingHours); return this; } /** *
* The scope of training to be performed when creating the solution version. The FULL option trains the
* solution version based on the entirety of the input solution's training data, while the UPDATE
* option processes only the data that has changed in comparison to the input solution. Choose UPDATE
* when you want to incrementally update your solution version instead of creating an entirely new one.
*
* The UPDATE option can only be used when you already have an active solution version created from the
* input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart
* recipe.
*
FULL option
* trains the solution version based on the entirety of the input solution's training data, while the
* UPDATE option processes only the data that has changed in comparison to the input solution.
* Choose UPDATE when you want to incrementally update your solution version instead of creating
* an entirely new one.
* The UPDATE option can only be used when you already have an active solution version created
* from the input solution using the FULL option and the input solution was trained with the
* User-Personalization recipe or the HRNN-Coldstart recipe.
*
* The scope of training to be performed when creating the solution version. The FULL option trains the
* solution version based on the entirety of the input solution's training data, while the UPDATE
* option processes only the data that has changed in comparison to the input solution. Choose UPDATE
* when you want to incrementally update your solution version instead of creating an entirely new one.
*
* The UPDATE option can only be used when you already have an active solution version created from the
* input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart
* recipe.
*
FULL option
* trains the solution version based on the entirety of the input solution's training data, while the
* UPDATE option processes only the data that has changed in comparison to the input solution.
* Choose UPDATE when you want to incrementally update your solution version instead of
* creating an entirely new one.
* The UPDATE option can only be used when you already have an active solution version created
* from the input solution using the FULL option and the input solution was trained with the
* User-Personalization recipe or the HRNN-Coldstart recipe.
*
* The scope of training to be performed when creating the solution version. The FULL option trains the
* solution version based on the entirety of the input solution's training data, while the UPDATE
* option processes only the data that has changed in comparison to the input solution. Choose UPDATE
* when you want to incrementally update your solution version instead of creating an entirely new one.
*
* The UPDATE option can only be used when you already have an active solution version created from the
* input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart
* recipe.
*
FULL option
* trains the solution version based on the entirety of the input solution's training data, while the
* UPDATE option processes only the data that has changed in comparison to the input solution.
* Choose UPDATE when you want to incrementally update your solution version instead of creating
* an entirely new one.
* The UPDATE option can only be used when you already have an active solution version created
* from the input solution using the FULL option and the input solution was trained with the
* User-Personalization recipe or the HRNN-Coldstart recipe.
*
* The scope of training to be performed when creating the solution version. The FULL option trains the
* solution version based on the entirety of the input solution's training data, while the UPDATE
* option processes only the data that has changed in comparison to the input solution. Choose UPDATE
* when you want to incrementally update your solution version instead of creating an entirely new one.
*
* The UPDATE option can only be used when you already have an active solution version created from the
* input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart
* recipe.
*
FULL option
* trains the solution version based on the entirety of the input solution's training data, while the
* UPDATE option processes only the data that has changed in comparison to the input solution.
* Choose UPDATE when you want to incrementally update your solution version instead of creating
* an entirely new one.
* The UPDATE option can only be used when you already have an active solution version created
* from the input solution using the FULL option and the input solution was trained with the
* User-Personalization recipe or the HRNN-Coldstart recipe.
*
* If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model. *
* * @param tunedHPOParams * If hyperparameter optimization was performed, contains the hyperparameter values of the best performing * model. */ public void setTunedHPOParams(TunedHPOParams tunedHPOParams) { this.tunedHPOParams = tunedHPOParams; } /** ** If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model. *
* * @return If hyperparameter optimization was performed, contains the hyperparameter values of the best performing * model. */ public TunedHPOParams getTunedHPOParams() { return this.tunedHPOParams; } /** ** If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model. *
* * @param tunedHPOParams * If hyperparameter optimization was performed, contains the hyperparameter values of the best performing * model. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withTunedHPOParams(TunedHPOParams tunedHPOParams) { setTunedHPOParams(tunedHPOParams); return this; } /** ** The status of the solution version. *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** The status of the solution version. *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** The status of the solution version. *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** A solution version can be in one of the following states: *
** CREATE PENDING *
** CREATE IN_PROGRESS *
** ACTIVE *
** CREATE FAILED *
** CREATE STOPPING *
** CREATE STOPPED *
** If training a solution version fails, the reason for the failure. *
* * @param failureReason * If training a solution version fails, the reason for the failure. */ public void setFailureReason(String failureReason) { this.failureReason = failureReason; } /** ** If training a solution version fails, the reason for the failure. *
* * @return If training a solution version fails, the reason for the failure. */ public String getFailureReason() { return this.failureReason; } /** ** If training a solution version fails, the reason for the failure. *
* * @param failureReason * If training a solution version fails, the reason for the failure. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withFailureReason(String failureReason) { setFailureReason(failureReason); return this; } /** ** The date and time (in Unix time) that this version of the solution was created. *
* * @param creationDateTime * The date and time (in Unix time) that this version of the solution was created. */ public void setCreationDateTime(java.util.Date creationDateTime) { this.creationDateTime = creationDateTime; } /** ** The date and time (in Unix time) that this version of the solution was created. *
* * @return The date and time (in Unix time) that this version of the solution was created. */ public java.util.Date getCreationDateTime() { return this.creationDateTime; } /** ** The date and time (in Unix time) that this version of the solution was created. *
* * @param creationDateTime * The date and time (in Unix time) that this version of the solution was created. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withCreationDateTime(java.util.Date creationDateTime) { setCreationDateTime(creationDateTime); return this; } /** ** The date and time (in Unix time) that the solution was last updated. *
* * @param lastUpdatedDateTime * The date and time (in Unix time) that the solution was last updated. */ public void setLastUpdatedDateTime(java.util.Date lastUpdatedDateTime) { this.lastUpdatedDateTime = lastUpdatedDateTime; } /** ** The date and time (in Unix time) that the solution was last updated. *
* * @return The date and time (in Unix time) that the solution was last updated. */ public java.util.Date getLastUpdatedDateTime() { return this.lastUpdatedDateTime; } /** ** The date and time (in Unix time) that the solution was last updated. *
* * @param lastUpdatedDateTime * The date and time (in Unix time) that the solution was last updated. * @return Returns a reference to this object so that method calls can be chained together. */ public SolutionVersion withLastUpdatedDateTime(java.util.Date lastUpdatedDateTime) { setLastUpdatedDateTime(lastUpdatedDateTime); 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 (getName() != null) sb.append("Name: ").append(getName()).append(","); if (getSolutionVersionArn() != null) sb.append("SolutionVersionArn: ").append(getSolutionVersionArn()).append(","); if (getSolutionArn() != null) sb.append("SolutionArn: ").append(getSolutionArn()).append(","); if (getPerformHPO() != null) sb.append("PerformHPO: ").append(getPerformHPO()).append(","); if (getPerformAutoML() != null) sb.append("PerformAutoML: ").append(getPerformAutoML()).append(","); if (getRecipeArn() != null) sb.append("RecipeArn: ").append(getRecipeArn()).append(","); if (getEventType() != null) sb.append("EventType: ").append(getEventType()).append(","); if (getDatasetGroupArn() != null) sb.append("DatasetGroupArn: ").append(getDatasetGroupArn()).append(","); if (getSolutionConfig() != null) sb.append("SolutionConfig: ").append(getSolutionConfig()).append(","); if (getTrainingHours() != null) sb.append("TrainingHours: ").append(getTrainingHours()).append(","); if (getTrainingMode() != null) sb.append("TrainingMode: ").append(getTrainingMode()).append(","); if (getTunedHPOParams() != null) sb.append("TunedHPOParams: ").append(getTunedHPOParams()).append(","); if (getStatus() != null) sb.append("Status: ").append(getStatus()).append(","); if (getFailureReason() != null) sb.append("FailureReason: ").append(getFailureReason()).append(","); if (getCreationDateTime() != null) sb.append("CreationDateTime: ").append(getCreationDateTime()).append(","); if (getLastUpdatedDateTime() != null) sb.append("LastUpdatedDateTime: ").append(getLastUpdatedDateTime()); sb.append("}"); return sb.toString(); } @Override public boolean equals(Object obj) { if (this == obj) return true; if (obj == null) return false; if (obj instanceof SolutionVersion == false) return false; SolutionVersion other = (SolutionVersion) obj; if (other.getName() == null ^ this.getName() == null) return false; if (other.getName() != null && other.getName().equals(this.getName()) == false) return false; if (other.getSolutionVersionArn() == null ^ this.getSolutionVersionArn() == null) return false; if (other.getSolutionVersionArn() != null && other.getSolutionVersionArn().equals(this.getSolutionVersionArn()) == false) return false; if (other.getSolutionArn() == null ^ this.getSolutionArn() == null) return false; if (other.getSolutionArn() != null && other.getSolutionArn().equals(this.getSolutionArn()) == false) return false; if (other.getPerformHPO() == null ^ this.getPerformHPO() == null) return false; if (other.getPerformHPO() != null && other.getPerformHPO().equals(this.getPerformHPO()) == false) return false; if (other.getPerformAutoML() == null ^ this.getPerformAutoML() == null) return false; if (other.getPerformAutoML() != null && other.getPerformAutoML().equals(this.getPerformAutoML()) == false) return false; if (other.getRecipeArn() == null ^ this.getRecipeArn() == null) return false; if (other.getRecipeArn() != null && other.getRecipeArn().equals(this.getRecipeArn()) == false) return false; if (other.getEventType() == null ^ this.getEventType() == null) return false; if (other.getEventType() != null && other.getEventType().equals(this.getEventType()) == false) return false; if (other.getDatasetGroupArn() == null ^ this.getDatasetGroupArn() == null) return false; if (other.getDatasetGroupArn() != null && other.getDatasetGroupArn().equals(this.getDatasetGroupArn()) == false) return false; if (other.getSolutionConfig() == null ^ this.getSolutionConfig() == null) return false; if (other.getSolutionConfig() != null && other.getSolutionConfig().equals(this.getSolutionConfig()) == false) return false; if (other.getTrainingHours() == null ^ this.getTrainingHours() == null) return false; if (other.getTrainingHours() != null && other.getTrainingHours().equals(this.getTrainingHours()) == false) return false; if (other.getTrainingMode() == null ^ this.getTrainingMode() == null) return false; if (other.getTrainingMode() != null && other.getTrainingMode().equals(this.getTrainingMode()) == false) return false; if (other.getTunedHPOParams() == null ^ this.getTunedHPOParams() == null) return false; if (other.getTunedHPOParams() != null && other.getTunedHPOParams().equals(this.getTunedHPOParams()) == false) return false; if (other.getStatus() == null ^ this.getStatus() == null) return false; if (other.getStatus() != null && other.getStatus().equals(this.getStatus()) == false) return false; if (other.getFailureReason() == null ^ this.getFailureReason() == null) return false; if (other.getFailureReason() != null && other.getFailureReason().equals(this.getFailureReason()) == false) return false; if (other.getCreationDateTime() == null ^ this.getCreationDateTime() == null) return false; if (other.getCreationDateTime() != null && other.getCreationDateTime().equals(this.getCreationDateTime()) == false) return false; if (other.getLastUpdatedDateTime() == null ^ this.getLastUpdatedDateTime() == null) return false; if (other.getLastUpdatedDateTime() != null && other.getLastUpdatedDateTime().equals(this.getLastUpdatedDateTime()) == false) return false; return true; } @Override public int hashCode() { final int prime = 31; int hashCode = 1; hashCode = prime * hashCode + ((getName() == null) ? 0 : getName().hashCode()); hashCode = prime * hashCode + ((getSolutionVersionArn() == null) ? 0 : getSolutionVersionArn().hashCode()); hashCode = prime * hashCode + ((getSolutionArn() == null) ? 0 : getSolutionArn().hashCode()); hashCode = prime * hashCode + ((getPerformHPO() == null) ? 0 : getPerformHPO().hashCode()); hashCode = prime * hashCode + ((getPerformAutoML() == null) ? 0 : getPerformAutoML().hashCode()); hashCode = prime * hashCode + ((getRecipeArn() == null) ? 0 : getRecipeArn().hashCode()); hashCode = prime * hashCode + ((getEventType() == null) ? 0 : getEventType().hashCode()); hashCode = prime * hashCode + ((getDatasetGroupArn() == null) ? 0 : getDatasetGroupArn().hashCode()); hashCode = prime * hashCode + ((getSolutionConfig() == null) ? 0 : getSolutionConfig().hashCode()); hashCode = prime * hashCode + ((getTrainingHours() == null) ? 0 : getTrainingHours().hashCode()); hashCode = prime * hashCode + ((getTrainingMode() == null) ? 0 : getTrainingMode().hashCode()); hashCode = prime * hashCode + ((getTunedHPOParams() == null) ? 0 : getTunedHPOParams().hashCode()); hashCode = prime * hashCode + ((getStatus() == null) ? 0 : getStatus().hashCode()); hashCode = prime * hashCode + ((getFailureReason() == null) ? 0 : getFailureReason().hashCode()); hashCode = prime * hashCode + ((getCreationDateTime() == null) ? 0 : getCreationDateTime().hashCode()); hashCode = prime * hashCode + ((getLastUpdatedDateTime() == null) ? 0 : getLastUpdatedDateTime().hashCode()); return hashCode; } @Override public SolutionVersion clone() { try { return (SolutionVersion) 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.personalize.model.transform.SolutionVersionMarshaller.getInstance().marshall(this, protocolMarshaller); } }