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/*
* Copyright 2016-2021 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.machinelearning.model;
import java.io.Serializable;
import javax.annotation.Generated;
import com.amazonaws.protocol.StructuredPojo;
import com.amazonaws.protocol.ProtocolMarshaller;
/**
*
* Represents the output of GetEvaluation operation.
*
*
* The content consists of the detailed metadata and data file information and the current status of the
* Evaluation.
*
*/
@Generated("com.amazonaws:aws-java-sdk-code-generator")
public class Evaluation implements Serializable, Cloneable, StructuredPojo {
/**
*
* The ID that is assigned to the Evaluation at creation.
*
*/
private String evaluationId;
/**
*
* The ID of the MLModel that is the focus of the evaluation.
*
*/
private String mLModelId;
/**
*
* The ID of the DataSource that is used to evaluate the MLModel.
*
*/
private String evaluationDataSourceId;
/**
*
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
*
*/
private String inputDataLocationS3;
/**
*
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS
* Identity and Access Management (IAM) user account.
*
*/
private String createdByIamUser;
/**
*
* The time that the Evaluation was created. The time is expressed in epoch time.
*
*/
private java.util.Date createdAt;
/**
*
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*
*/
private java.util.Date lastUpdatedAt;
/**
*
* A user-supplied name or description of the Evaluation.
*
*/
private String name;
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*/
private String status;
/**
*
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the MLModel:
*
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure
* performance. RMSE measures the difference between predicted and actual values for a single variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*
*/
private PerformanceMetrics performanceMetrics;
/**
*
* A description of the most recent details about evaluating the MLModel.
*
*/
private String message;
private Long computeTime;
private java.util.Date finishedAt;
private java.util.Date startedAt;
/**
*
* The ID that is assigned to the Evaluation at creation.
*
*
* @param evaluationId
* The ID that is assigned to the Evaluation at creation.
*/
public void setEvaluationId(String evaluationId) {
this.evaluationId = evaluationId;
}
/**
*
* The ID that is assigned to the Evaluation at creation.
*
*
* @return The ID that is assigned to the Evaluation at creation.
*/
public String getEvaluationId() {
return this.evaluationId;
}
/**
*
* The ID that is assigned to the Evaluation at creation.
*
*
* @param evaluationId
* The ID that is assigned to the Evaluation at creation.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withEvaluationId(String evaluationId) {
setEvaluationId(evaluationId);
return this;
}
/**
*
* The ID of the MLModel that is the focus of the evaluation.
*
*
* @param mLModelId
* The ID of the MLModel that is the focus of the evaluation.
*/
public void setMLModelId(String mLModelId) {
this.mLModelId = mLModelId;
}
/**
*
* The ID of the MLModel that is the focus of the evaluation.
*
*
* @return The ID of the MLModel that is the focus of the evaluation.
*/
public String getMLModelId() {
return this.mLModelId;
}
/**
*
* The ID of the MLModel that is the focus of the evaluation.
*
*
* @param mLModelId
* The ID of the MLModel that is the focus of the evaluation.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withMLModelId(String mLModelId) {
setMLModelId(mLModelId);
return this;
}
/**
*
* The ID of the DataSource that is used to evaluate the MLModel.
*
*
* @param evaluationDataSourceId
* The ID of the DataSource that is used to evaluate the MLModel.
*/
public void setEvaluationDataSourceId(String evaluationDataSourceId) {
this.evaluationDataSourceId = evaluationDataSourceId;
}
/**
*
* The ID of the DataSource that is used to evaluate the MLModel.
*
*
* @return The ID of the DataSource that is used to evaluate the MLModel.
*/
public String getEvaluationDataSourceId() {
return this.evaluationDataSourceId;
}
/**
*
* The ID of the DataSource that is used to evaluate the MLModel.
*
*
* @param evaluationDataSourceId
* The ID of the DataSource that is used to evaluate the MLModel.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withEvaluationDataSourceId(String evaluationDataSourceId) {
setEvaluationDataSourceId(evaluationDataSourceId);
return this;
}
/**
*
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
*
*
* @param inputDataLocationS3
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the
* evaluation.
*/
public void setInputDataLocationS3(String inputDataLocationS3) {
this.inputDataLocationS3 = inputDataLocationS3;
}
/**
*
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
*
*
* @return The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the
* evaluation.
*/
public String getInputDataLocationS3() {
return this.inputDataLocationS3;
}
/**
*
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.
*
*
* @param inputDataLocationS3
* The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the
* evaluation.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withInputDataLocationS3(String inputDataLocationS3) {
setInputDataLocationS3(inputDataLocationS3);
return this;
}
/**
*
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS
* Identity and Access Management (IAM) user account.
*
*
* @param createdByIamUser
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an
* AWS Identity and Access Management (IAM) user account.
*/
public void setCreatedByIamUser(String createdByIamUser) {
this.createdByIamUser = createdByIamUser;
}
/**
*
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS
* Identity and Access Management (IAM) user account.
*
*
* @return The AWS user account that invoked the evaluation. The account type can be either an AWS root account or
* an AWS Identity and Access Management (IAM) user account.
*/
public String getCreatedByIamUser() {
return this.createdByIamUser;
}
/**
*
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an AWS
* Identity and Access Management (IAM) user account.
*
*
* @param createdByIamUser
* The AWS user account that invoked the evaluation. The account type can be either an AWS root account or an
* AWS Identity and Access Management (IAM) user account.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withCreatedByIamUser(String createdByIamUser) {
setCreatedByIamUser(createdByIamUser);
return this;
}
/**
*
* The time that the Evaluation was created. The time is expressed in epoch time.
*
*
* @param createdAt
* The time that the Evaluation was created. The time is expressed in epoch time.
*/
public void setCreatedAt(java.util.Date createdAt) {
this.createdAt = createdAt;
}
/**
*
* The time that the Evaluation was created. The time is expressed in epoch time.
*
*
* @return The time that the Evaluation was created. The time is expressed in epoch time.
*/
public java.util.Date getCreatedAt() {
return this.createdAt;
}
/**
*
* The time that the Evaluation was created. The time is expressed in epoch time.
*
*
* @param createdAt
* The time that the Evaluation was created. The time is expressed in epoch time.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withCreatedAt(java.util.Date createdAt) {
setCreatedAt(createdAt);
return this;
}
/**
*
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*
*
* @param lastUpdatedAt
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*/
public void setLastUpdatedAt(java.util.Date lastUpdatedAt) {
this.lastUpdatedAt = lastUpdatedAt;
}
/**
*
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*
*
* @return The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*/
public java.util.Date getLastUpdatedAt() {
return this.lastUpdatedAt;
}
/**
*
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
*
*
* @param lastUpdatedAt
* The time of the most recent edit to the Evaluation. The time is expressed in epoch time.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withLastUpdatedAt(java.util.Date lastUpdatedAt) {
setLastUpdatedAt(lastUpdatedAt);
return this;
}
/**
*
* A user-supplied name or description of the Evaluation.
*
*
* @param name
* A user-supplied name or description of the Evaluation.
*/
public void setName(String name) {
this.name = name;
}
/**
*
* A user-supplied name or description of the Evaluation.
*
*
* @return A user-supplied name or description of the Evaluation.
*/
public String getName() {
return this.name;
}
/**
*
* A user-supplied name or description of the Evaluation.
*
*
* @param name
* A user-supplied name or description of the Evaluation.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withName(String name) {
setName(name);
return this;
}
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*
* @param status
* The status of the evaluation. This element can have one of the following values:
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is
* not usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
* @see EntityStatus
*/
public void setStatus(String status) {
this.status = status;
}
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*
* @return The status of the evaluation. This element can have one of the following values:
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It
* is not usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
* @see EntityStatus
*/
public String getStatus() {
return this.status;
}
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*
* @param status
* The status of the evaluation. This element can have one of the following values:
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is
* not usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
* @return Returns a reference to this object so that method calls can be chained together.
* @see EntityStatus
*/
public Evaluation withStatus(String status) {
setStatus(status);
return this;
}
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*
* @param status
* The status of the evaluation. This element can have one of the following values:
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is
* not usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
* @see EntityStatus
*/
public void setStatus(EntityStatus status) {
withStatus(status);
}
/**
*
* The status of the evaluation. This element can have one of the following values:
*
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is not
* usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
*
*
* @param status
* The status of the evaluation. This element can have one of the following values:
*
* -
PENDING - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an
* MLModel.
* -
INPROGRESS - The evaluation is underway.
* -
FAILED - The request to evaluate an MLModel did not run to completion. It is
* not usable.
* -
COMPLETED - The evaluation process completed successfully.
* -
DELETED - The Evaluation is marked as deleted. It is not usable.
* @return Returns a reference to this object so that method calls can be chained together.
* @see EntityStatus
*/
public Evaluation withStatus(EntityStatus status) {
this.status = status.toString();
return this;
}
/**
*
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the MLModel:
*
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure
* performance. RMSE measures the difference between predicted and actual values for a single variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*
*
* @param performanceMetrics
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the
* MLModel:
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure
* performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to
* measure performance. RMSE measures the difference between predicted and actual values for a single
* variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*/
public void setPerformanceMetrics(PerformanceMetrics performanceMetrics) {
this.performanceMetrics = performanceMetrics;
}
/**
*
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the MLModel:
*
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure
* performance. RMSE measures the difference between predicted and actual values for a single variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*
*
* @return Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the
* MLModel:
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure
* performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to
* measure performance. RMSE measures the difference between predicted and actual values for a single
* variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure
* performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*/
public PerformanceMetrics getPerformanceMetrics() {
return this.performanceMetrics;
}
/**
*
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the MLModel:
*
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to measure
* performance. RMSE measures the difference between predicted and actual values for a single variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
*
*
* @param performanceMetrics
* Measurements of how well the MLModel performed, using observations referenced by the
* DataSource. One of the following metrics is returned, based on the type of the
* MLModel:
*
* -
*
* BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique to measure
* performance.
*
*
* -
*
* RegressionRMSE: A regression MLModel uses the Root Mean Square Error (RMSE) technique to
* measure performance. RMSE measures the difference between predicted and actual values for a single
* variable.
*
*
* -
*
* MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique to measure performance.
*
*
*
*
* For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withPerformanceMetrics(PerformanceMetrics performanceMetrics) {
setPerformanceMetrics(performanceMetrics);
return this;
}
/**
*
* A description of the most recent details about evaluating the MLModel.
*
*
* @param message
* A description of the most recent details about evaluating the MLModel.
*/
public void setMessage(String message) {
this.message = message;
}
/**
*
* A description of the most recent details about evaluating the MLModel.
*
*
* @return A description of the most recent details about evaluating the MLModel.
*/
public String getMessage() {
return this.message;
}
/**
*
* A description of the most recent details about evaluating the MLModel.
*
*
* @param message
* A description of the most recent details about evaluating the MLModel.
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withMessage(String message) {
setMessage(message);
return this;
}
/**
* @param computeTime
*/
public void setComputeTime(Long computeTime) {
this.computeTime = computeTime;
}
/**
* @return
*/
public Long getComputeTime() {
return this.computeTime;
}
/**
* @param computeTime
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withComputeTime(Long computeTime) {
setComputeTime(computeTime);
return this;
}
/**
* @param finishedAt
*/
public void setFinishedAt(java.util.Date finishedAt) {
this.finishedAt = finishedAt;
}
/**
* @return
*/
public java.util.Date getFinishedAt() {
return this.finishedAt;
}
/**
* @param finishedAt
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withFinishedAt(java.util.Date finishedAt) {
setFinishedAt(finishedAt);
return this;
}
/**
* @param startedAt
*/
public void setStartedAt(java.util.Date startedAt) {
this.startedAt = startedAt;
}
/**
* @return
*/
public java.util.Date getStartedAt() {
return this.startedAt;
}
/**
* @param startedAt
* @return Returns a reference to this object so that method calls can be chained together.
*/
public Evaluation withStartedAt(java.util.Date startedAt) {
setStartedAt(startedAt);
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 (getEvaluationId() != null)
sb.append("EvaluationId: ").append(getEvaluationId()).append(",");
if (getMLModelId() != null)
sb.append("MLModelId: ").append(getMLModelId()).append(",");
if (getEvaluationDataSourceId() != null)
sb.append("EvaluationDataSourceId: ").append(getEvaluationDataSourceId()).append(",");
if (getInputDataLocationS3() != null)
sb.append("InputDataLocationS3: ").append(getInputDataLocationS3()).append(",");
if (getCreatedByIamUser() != null)
sb.append("CreatedByIamUser: ").append(getCreatedByIamUser()).append(",");
if (getCreatedAt() != null)
sb.append("CreatedAt: ").append(getCreatedAt()).append(",");
if (getLastUpdatedAt() != null)
sb.append("LastUpdatedAt: ").append(getLastUpdatedAt()).append(",");
if (getName() != null)
sb.append("Name: ").append(getName()).append(",");
if (getStatus() != null)
sb.append("Status: ").append(getStatus()).append(",");
if (getPerformanceMetrics() != null)
sb.append("PerformanceMetrics: ").append(getPerformanceMetrics()).append(",");
if (getMessage() != null)
sb.append("Message: ").append(getMessage()).append(",");
if (getComputeTime() != null)
sb.append("ComputeTime: ").append(getComputeTime()).append(",");
if (getFinishedAt() != null)
sb.append("FinishedAt: ").append(getFinishedAt()).append(",");
if (getStartedAt() != null)
sb.append("StartedAt: ").append(getStartedAt());
sb.append("}");
return sb.toString();
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (obj instanceof Evaluation == false)
return false;
Evaluation other = (Evaluation) obj;
if (other.getEvaluationId() == null ^ this.getEvaluationId() == null)
return false;
if (other.getEvaluationId() != null && other.getEvaluationId().equals(this.getEvaluationId()) == false)
return false;
if (other.getMLModelId() == null ^ this.getMLModelId() == null)
return false;
if (other.getMLModelId() != null && other.getMLModelId().equals(this.getMLModelId()) == false)
return false;
if (other.getEvaluationDataSourceId() == null ^ this.getEvaluationDataSourceId() == null)
return false;
if (other.getEvaluationDataSourceId() != null && other.getEvaluationDataSourceId().equals(this.getEvaluationDataSourceId()) == false)
return false;
if (other.getInputDataLocationS3() == null ^ this.getInputDataLocationS3() == null)
return false;
if (other.getInputDataLocationS3() != null && other.getInputDataLocationS3().equals(this.getInputDataLocationS3()) == false)
return false;
if (other.getCreatedByIamUser() == null ^ this.getCreatedByIamUser() == null)
return false;
if (other.getCreatedByIamUser() != null && other.getCreatedByIamUser().equals(this.getCreatedByIamUser()) == false)
return false;
if (other.getCreatedAt() == null ^ this.getCreatedAt() == null)
return false;
if (other.getCreatedAt() != null && other.getCreatedAt().equals(this.getCreatedAt()) == false)
return false;
if (other.getLastUpdatedAt() == null ^ this.getLastUpdatedAt() == null)
return false;
if (other.getLastUpdatedAt() != null && other.getLastUpdatedAt().equals(this.getLastUpdatedAt()) == false)
return false;
if (other.getName() == null ^ this.getName() == null)
return false;
if (other.getName() != null && other.getName().equals(this.getName()) == 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.getPerformanceMetrics() == null ^ this.getPerformanceMetrics() == null)
return false;
if (other.getPerformanceMetrics() != null && other.getPerformanceMetrics().equals(this.getPerformanceMetrics()) == false)
return false;
if (other.getMessage() == null ^ this.getMessage() == null)
return false;
if (other.getMessage() != null && other.getMessage().equals(this.getMessage()) == false)
return false;
if (other.getComputeTime() == null ^ this.getComputeTime() == null)
return false;
if (other.getComputeTime() != null && other.getComputeTime().equals(this.getComputeTime()) == false)
return false;
if (other.getFinishedAt() == null ^ this.getFinishedAt() == null)
return false;
if (other.getFinishedAt() != null && other.getFinishedAt().equals(this.getFinishedAt()) == false)
return false;
if (other.getStartedAt() == null ^ this.getStartedAt() == null)
return false;
if (other.getStartedAt() != null && other.getStartedAt().equals(this.getStartedAt()) == false)
return false;
return true;
}
@Override
public int hashCode() {
final int prime = 31;
int hashCode = 1;
hashCode = prime * hashCode + ((getEvaluationId() == null) ? 0 : getEvaluationId().hashCode());
hashCode = prime * hashCode + ((getMLModelId() == null) ? 0 : getMLModelId().hashCode());
hashCode = prime * hashCode + ((getEvaluationDataSourceId() == null) ? 0 : getEvaluationDataSourceId().hashCode());
hashCode = prime * hashCode + ((getInputDataLocationS3() == null) ? 0 : getInputDataLocationS3().hashCode());
hashCode = prime * hashCode + ((getCreatedByIamUser() == null) ? 0 : getCreatedByIamUser().hashCode());
hashCode = prime * hashCode + ((getCreatedAt() == null) ? 0 : getCreatedAt().hashCode());
hashCode = prime * hashCode + ((getLastUpdatedAt() == null) ? 0 : getLastUpdatedAt().hashCode());
hashCode = prime * hashCode + ((getName() == null) ? 0 : getName().hashCode());
hashCode = prime * hashCode + ((getStatus() == null) ? 0 : getStatus().hashCode());
hashCode = prime * hashCode + ((getPerformanceMetrics() == null) ? 0 : getPerformanceMetrics().hashCode());
hashCode = prime * hashCode + ((getMessage() == null) ? 0 : getMessage().hashCode());
hashCode = prime * hashCode + ((getComputeTime() == null) ? 0 : getComputeTime().hashCode());
hashCode = prime * hashCode + ((getFinishedAt() == null) ? 0 : getFinishedAt().hashCode());
hashCode = prime * hashCode + ((getStartedAt() == null) ? 0 : getStartedAt().hashCode());
return hashCode;
}
@Override
public Evaluation clone() {
try {
return (Evaluation) 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.machinelearning.model.transform.EvaluationMarshaller.getInstance().marshall(this, protocolMarshaller);
}
}