// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.

/// <p> Represents the output of <code>GetEvaluation</code> operation. </p>
/// <p>The content consists of the detailed metadata and data file information and the current status of the <code>Evaluation</code>.</p>
#[non_exhaustive]
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::fmt::Debug)]
pub struct Evaluation {
    /// <p>The ID that is assigned to the <code>Evaluation</code> at creation.</p>
    pub evaluation_id: ::std::option::Option<::std::string::String>,
    /// <p>The ID of the <code>MLModel</code> that is the focus of the evaluation.</p>
    pub ml_model_id: ::std::option::Option<::std::string::String>,
    /// <p>The ID of the <code>DataSource</code> that is used to evaluate the <code>MLModel</code>.</p>
    pub evaluation_data_source_id: ::std::option::Option<::std::string::String>,
    /// <p>The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.</p>
    pub input_data_location_s3: ::std::option::Option<::std::string::String>,
    /// <p>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.</p>
    pub created_by_iam_user: ::std::option::Option<::std::string::String>,
    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
    pub created_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
    pub last_updated_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    /// <p>A user-supplied name or description of the <code>Evaluation</code>. </p>
    pub name: ::std::option::Option<::std::string::String>,
    /// <p>The status of the evaluation. This element can have one of the following values:</p>
    /// <ul>
    /// <li> <p> <code>PENDING</code> - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li>
    /// <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li>
    /// <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li>
    /// <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li>
    /// <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li>
    /// </ul>
    pub status: ::std::option::Option<crate::types::EntityStatus>,
    /// <p>Measurements of how well the <code>MLModel</code> performed, using observations referenced by the <code>DataSource</code>. One of the following metrics is returned, based on the type of the <code>MLModel</code>: </p>
    /// <ul>
    /// <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li>
    /// <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li>
    /// <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li>
    /// </ul>
    /// <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>
    pub performance_metrics: ::std::option::Option<crate::types::PerformanceMetrics>,
    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
    pub message: ::std::option::Option<::std::string::String>,
    /// <p>Long integer type that is a 64-bit signed number.</p>
    pub compute_time: ::std::option::Option<i64>,
    /// <p>A timestamp represented in epoch time.</p>
    pub finished_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    /// <p>A timestamp represented in epoch time.</p>
    pub started_at: ::std::option::Option<::aws_smithy_types::DateTime>,
}
impl Evaluation {
    /// <p>The ID that is assigned to the <code>Evaluation</code> at creation.</p>
    pub fn evaluation_id(&self) -> ::std::option::Option<&str> {
        self.evaluation_id.as_deref()
    }
    /// <p>The ID of the <code>MLModel</code> that is the focus of the evaluation.</p>
    pub fn ml_model_id(&self) -> ::std::option::Option<&str> {
        self.ml_model_id.as_deref()
    }
    /// <p>The ID of the <code>DataSource</code> that is used to evaluate the <code>MLModel</code>.</p>
    pub fn evaluation_data_source_id(&self) -> ::std::option::Option<&str> {
        self.evaluation_data_source_id.as_deref()
    }
    /// <p>The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.</p>
    pub fn input_data_location_s3(&self) -> ::std::option::Option<&str> {
        self.input_data_location_s3.as_deref()
    }
    /// <p>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.</p>
    pub fn created_by_iam_user(&self) -> ::std::option::Option<&str> {
        self.created_by_iam_user.as_deref()
    }
    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
    pub fn created_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
        self.created_at.as_ref()
    }
    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
    pub fn last_updated_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
        self.last_updated_at.as_ref()
    }
    /// <p>A user-supplied name or description of the <code>Evaluation</code>. </p>
    pub fn name(&self) -> ::std::option::Option<&str> {
        self.name.as_deref()
    }
    /// <p>The status of the evaluation. This element can have one of the following values:</p>
    /// <ul>
    /// <li> <p> <code>PENDING</code> - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li>
    /// <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li>
    /// <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li>
    /// <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li>
    /// <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li>
    /// </ul>
    pub fn status(&self) -> ::std::option::Option<&crate::types::EntityStatus> {
        self.status.as_ref()
    }
    /// <p>Measurements of how well the <code>MLModel</code> performed, using observations referenced by the <code>DataSource</code>. One of the following metrics is returned, based on the type of the <code>MLModel</code>: </p>
    /// <ul>
    /// <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li>
    /// <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li>
    /// <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li>
    /// </ul>
    /// <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>
    pub fn performance_metrics(&self) -> ::std::option::Option<&crate::types::PerformanceMetrics> {
        self.performance_metrics.as_ref()
    }
    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
    pub fn message(&self) -> ::std::option::Option<&str> {
        self.message.as_deref()
    }
    /// <p>Long integer type that is a 64-bit signed number.</p>
    pub fn compute_time(&self) -> ::std::option::Option<i64> {
        self.compute_time
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn finished_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
        self.finished_at.as_ref()
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn started_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
        self.started_at.as_ref()
    }
}
impl Evaluation {
    /// Creates a new builder-style object to manufacture [`Evaluation`](crate::types::Evaluation).
    pub fn builder() -> crate::types::builders::EvaluationBuilder {
        crate::types::builders::EvaluationBuilder::default()
    }
}

/// A builder for [`Evaluation`](crate::types::Evaluation).
#[non_exhaustive]
#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default, ::std::fmt::Debug)]
pub struct EvaluationBuilder {
    pub(crate) evaluation_id: ::std::option::Option<::std::string::String>,
    pub(crate) ml_model_id: ::std::option::Option<::std::string::String>,
    pub(crate) evaluation_data_source_id: ::std::option::Option<::std::string::String>,
    pub(crate) input_data_location_s3: ::std::option::Option<::std::string::String>,
    pub(crate) created_by_iam_user: ::std::option::Option<::std::string::String>,
    pub(crate) created_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    pub(crate) last_updated_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    pub(crate) name: ::std::option::Option<::std::string::String>,
    pub(crate) status: ::std::option::Option<crate::types::EntityStatus>,
    pub(crate) performance_metrics: ::std::option::Option<crate::types::PerformanceMetrics>,
    pub(crate) message: ::std::option::Option<::std::string::String>,
    pub(crate) compute_time: ::std::option::Option<i64>,
    pub(crate) finished_at: ::std::option::Option<::aws_smithy_types::DateTime>,
    pub(crate) started_at: ::std::option::Option<::aws_smithy_types::DateTime>,
}
impl EvaluationBuilder {
    /// <p>The ID that is assigned to the <code>Evaluation</code> at creation.</p>
    pub fn evaluation_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.evaluation_id = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The ID that is assigned to the <code>Evaluation</code> at creation.</p>
    pub fn set_evaluation_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.evaluation_id = input;
        self
    }
    /// <p>The ID that is assigned to the <code>Evaluation</code> at creation.</p>
    pub fn get_evaluation_id(&self) -> &::std::option::Option<::std::string::String> {
        &self.evaluation_id
    }
    /// <p>The ID of the <code>MLModel</code> that is the focus of the evaluation.</p>
    pub fn ml_model_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.ml_model_id = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The ID of the <code>MLModel</code> that is the focus of the evaluation.</p>
    pub fn set_ml_model_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.ml_model_id = input;
        self
    }
    /// <p>The ID of the <code>MLModel</code> that is the focus of the evaluation.</p>
    pub fn get_ml_model_id(&self) -> &::std::option::Option<::std::string::String> {
        &self.ml_model_id
    }
    /// <p>The ID of the <code>DataSource</code> that is used to evaluate the <code>MLModel</code>.</p>
    pub fn evaluation_data_source_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.evaluation_data_source_id = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The ID of the <code>DataSource</code> that is used to evaluate the <code>MLModel</code>.</p>
    pub fn set_evaluation_data_source_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.evaluation_data_source_id = input;
        self
    }
    /// <p>The ID of the <code>DataSource</code> that is used to evaluate the <code>MLModel</code>.</p>
    pub fn get_evaluation_data_source_id(&self) -> &::std::option::Option<::std::string::String> {
        &self.evaluation_data_source_id
    }
    /// <p>The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.</p>
    pub fn input_data_location_s3(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.input_data_location_s3 = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.</p>
    pub fn set_input_data_location_s3(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.input_data_location_s3 = input;
        self
    }
    /// <p>The location and name of the data in Amazon Simple Storage Server (Amazon S3) that is used in the evaluation.</p>
    pub fn get_input_data_location_s3(&self) -> &::std::option::Option<::std::string::String> {
        &self.input_data_location_s3
    }
    /// <p>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.</p>
    pub fn created_by_iam_user(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.created_by_iam_user = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>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.</p>
    pub fn set_created_by_iam_user(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.created_by_iam_user = input;
        self
    }
    /// <p>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.</p>
    pub fn get_created_by_iam_user(&self) -> &::std::option::Option<::std::string::String> {
        &self.created_by_iam_user
    }
    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
    pub fn created_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
        self.created_at = ::std::option::Option::Some(input);
        self
    }
    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
    pub fn set_created_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
        self.created_at = input;
        self
    }
    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
    pub fn get_created_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
        &self.created_at
    }
    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
    pub fn last_updated_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
        self.last_updated_at = ::std::option::Option::Some(input);
        self
    }
    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
    pub fn set_last_updated_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
        self.last_updated_at = input;
        self
    }
    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
    pub fn get_last_updated_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
        &self.last_updated_at
    }
    /// <p>A user-supplied name or description of the <code>Evaluation</code>. </p>
    pub fn name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.name = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>A user-supplied name or description of the <code>Evaluation</code>. </p>
    pub fn set_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.name = input;
        self
    }
    /// <p>A user-supplied name or description of the <code>Evaluation</code>. </p>
    pub fn get_name(&self) -> &::std::option::Option<::std::string::String> {
        &self.name
    }
    /// <p>The status of the evaluation. This element can have one of the following values:</p>
    /// <ul>
    /// <li> <p> <code>PENDING</code> - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li>
    /// <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li>
    /// <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li>
    /// <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li>
    /// <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li>
    /// </ul>
    pub fn status(mut self, input: crate::types::EntityStatus) -> Self {
        self.status = ::std::option::Option::Some(input);
        self
    }
    /// <p>The status of the evaluation. This element can have one of the following values:</p>
    /// <ul>
    /// <li> <p> <code>PENDING</code> - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li>
    /// <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li>
    /// <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li>
    /// <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li>
    /// <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li>
    /// </ul>
    pub fn set_status(mut self, input: ::std::option::Option<crate::types::EntityStatus>) -> Self {
        self.status = input;
        self
    }
    /// <p>The status of the evaluation. This element can have one of the following values:</p>
    /// <ul>
    /// <li> <p> <code>PENDING</code> - Amazon Machine Learning (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p> </li>
    /// <li> <p> <code>INPROGRESS</code> - The evaluation is underway.</p> </li>
    /// <li> <p> <code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p> </li>
    /// <li> <p> <code>COMPLETED</code> - The evaluation process completed successfully.</p> </li>
    /// <li> <p> <code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p> </li>
    /// </ul>
    pub fn get_status(&self) -> &::std::option::Option<crate::types::EntityStatus> {
        &self.status
    }
    /// <p>Measurements of how well the <code>MLModel</code> performed, using observations referenced by the <code>DataSource</code>. One of the following metrics is returned, based on the type of the <code>MLModel</code>: </p>
    /// <ul>
    /// <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li>
    /// <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li>
    /// <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li>
    /// </ul>
    /// <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>
    pub fn performance_metrics(mut self, input: crate::types::PerformanceMetrics) -> Self {
        self.performance_metrics = ::std::option::Option::Some(input);
        self
    }
    /// <p>Measurements of how well the <code>MLModel</code> performed, using observations referenced by the <code>DataSource</code>. One of the following metrics is returned, based on the type of the <code>MLModel</code>: </p>
    /// <ul>
    /// <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li>
    /// <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li>
    /// <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li>
    /// </ul>
    /// <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>
    pub fn set_performance_metrics(mut self, input: ::std::option::Option<crate::types::PerformanceMetrics>) -> Self {
        self.performance_metrics = input;
        self
    }
    /// <p>Measurements of how well the <code>MLModel</code> performed, using observations referenced by the <code>DataSource</code>. One of the following metrics is returned, based on the type of the <code>MLModel</code>: </p>
    /// <ul>
    /// <li> <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance. </p> </li>
    /// <li> <p>RegressionRMSE: A regression <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.</p> </li>
    /// <li> <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance. </p> </li>
    /// </ul>
    /// <p> For more information about performance metrics, please see the <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine Learning Developer Guide</a>. </p>
    pub fn get_performance_metrics(&self) -> &::std::option::Option<crate::types::PerformanceMetrics> {
        &self.performance_metrics
    }
    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
    pub fn message(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.message = ::std::option::Option::Some(input.into());
        self
    }
    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
    pub fn set_message(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.message = input;
        self
    }
    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
    pub fn get_message(&self) -> &::std::option::Option<::std::string::String> {
        &self.message
    }
    /// <p>Long integer type that is a 64-bit signed number.</p>
    pub fn compute_time(mut self, input: i64) -> Self {
        self.compute_time = ::std::option::Option::Some(input);
        self
    }
    /// <p>Long integer type that is a 64-bit signed number.</p>
    pub fn set_compute_time(mut self, input: ::std::option::Option<i64>) -> Self {
        self.compute_time = input;
        self
    }
    /// <p>Long integer type that is a 64-bit signed number.</p>
    pub fn get_compute_time(&self) -> &::std::option::Option<i64> {
        &self.compute_time
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn finished_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
        self.finished_at = ::std::option::Option::Some(input);
        self
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn set_finished_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
        self.finished_at = input;
        self
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn get_finished_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
        &self.finished_at
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn started_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
        self.started_at = ::std::option::Option::Some(input);
        self
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn set_started_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
        self.started_at = input;
        self
    }
    /// <p>A timestamp represented in epoch time.</p>
    pub fn get_started_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
        &self.started_at
    }
    /// Consumes the builder and constructs a [`Evaluation`](crate::types::Evaluation).
    pub fn build(self) -> crate::types::Evaluation {
        crate::types::Evaluation {
            evaluation_id: self.evaluation_id,
            ml_model_id: self.ml_model_id,
            evaluation_data_source_id: self.evaluation_data_source_id,
            input_data_location_s3: self.input_data_location_s3,
            created_by_iam_user: self.created_by_iam_user,
            created_at: self.created_at,
            last_updated_at: self.last_updated_at,
            name: self.name,
            status: self.status,
            performance_metrics: self.performance_metrics,
            message: self.message,
            compute_time: self.compute_time,
            finished_at: self.finished_at,
            started_at: self.started_at,
        }
    }
}