com.amazonaws.services.sagemaker.model.FinalHyperParameterTuningJobObjectiveMetric 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;
/**
*
* Shows the latest objective metric emitted by a training job that was launched by a hyperparameter tuning job. You
* define the objective metric in the HyperParameterTuningJobObjective parameter of HyperParameterTuningJobConfig.
*
*
* @see AWS API Documentation
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class FinalHyperParameterTuningJobObjectiveMetric implements Serializable, Cloneable, StructuredPojo {
/**
*
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
*
*/
private String type;
/**
*
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the
* metrics for XGBoost as an
* example. You can also use a custom algorithm for training and define your own metrics. For more information, see
*
* Define metrics and environment variables.
*
*/
private String metricName;
/**
*
* The value of the objective metric.
*
*/
private Float value;
/**
*
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
*
*
* @param type
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
* @see HyperParameterTuningJobObjectiveType
*/
public void setType(String type) {
this.type = type;
}
/**
*
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
*
*
* @return Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
* @see HyperParameterTuningJobObjectiveType
*/
public String getType() {
return this.type;
}
/**
*
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
*
*
* @param type
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningJobObjectiveType
*/
public FinalHyperParameterTuningJobObjectiveMetric withType(String type) {
setType(type);
return this;
}
/**
*
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
*
*
* @param type
* Select if you want to minimize or maximize the objective metric during hyperparameter tuning.
* @return Returns a reference to this object so that method calls can be chained together.
* @see HyperParameterTuningJobObjectiveType
*/
public FinalHyperParameterTuningJobObjectiveMetric withType(HyperParameterTuningJobObjectiveType type) {
this.type = type.toString();
return this;
}
/**
*
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the
* metrics for XGBoost as an
* example. You can also use a custom algorithm for training and define your own metrics. For more information, see
*
* Define metrics and environment variables.
*
*
* @param metricName
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm.
* See the metrics for
* XGBoost as an example. You can also use a custom algorithm for training and define your own metrics.
* For more information, see Define metrics and environment variables.
*/
public void setMetricName(String metricName) {
this.metricName = metricName;
}
/**
*
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the
* metrics for XGBoost as an
* example. You can also use a custom algorithm for training and define your own metrics. For more information, see
*
* Define metrics and environment variables.
*
*
* @return The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm.
* See the metrics for
* XGBoost as an example. You can also use a custom algorithm for training and define your own metrics.
* For more information, see Define metrics and environment variables.
*/
public String getMetricName() {
return this.metricName;
}
/**
*
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the
* metrics for XGBoost as an
* example. You can also use a custom algorithm for training and define your own metrics. For more information, see
*
* Define metrics and environment variables.
*
*
* @param metricName
* The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm.
* See the metrics for
* XGBoost as an example. You can also use a custom algorithm for training and define your own metrics.
* For more information, see Define metrics and environment variables.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public FinalHyperParameterTuningJobObjectiveMetric withMetricName(String metricName) {
setMetricName(metricName);
return this;
}
/**
*
* The value of the objective metric.
*
*
* @param value
* The value of the objective metric.
*/
public void setValue(Float value) {
this.value = value;
}
/**
*
* The value of the objective metric.
*
*
* @return The value of the objective metric.
*/
public Float getValue() {
return this.value;
}
/**
*
* The value of the objective metric.
*
*
* @param value
* The value of the objective metric.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public FinalHyperParameterTuningJobObjectiveMetric withValue(Float value) {
setValue(value);
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 (getType() != null)
sb.append("Type: ").append(getType()).append(",");
if (getMetricName() != null)
sb.append("MetricName: ").append(getMetricName()).append(",");
if (getValue() != null)
sb.append("Value: ").append(getValue());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof FinalHyperParameterTuningJobObjectiveMetric == false)
return false;
FinalHyperParameterTuningJobObjectiveMetric other = (FinalHyperParameterTuningJobObjectiveMetric) obj;
if (other.getType() == null ^ this.getType() == null)
return false;
if (other.getType() != null && other.getType().equals(this.getType()) == false)
return false;
if (other.getMetricName() == null ^ this.getMetricName() == null)
return false;
if (other.getMetricName() != null && other.getMetricName().equals(this.getMetricName()) == false)
return false;
if (other.getValue() == null ^ this.getValue() == null)
return false;
if (other.getValue() != null && other.getValue().equals(this.getValue()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getType() == null) ? 0 : getType().hashCode());
hashCode = prime * hashCode + ((getMetricName() == null) ? 0 : getMetricName().hashCode());
hashCode = prime * hashCode + ((getValue() == null) ? 0 : getValue().hashCode());
return hashCode;
}
@Override
public FinalHyperParameterTuningJobObjectiveMetric clone() {
try {
return (FinalHyperParameterTuningJobObjectiveMetric) 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.FinalHyperParameterTuningJobObjectiveMetricMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}