aws_sdk_machinelearning/operation/get_evaluation/
_get_evaluation_output.rs

1// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
2
3/// <p>Represents the output of a <code>GetEvaluation</code> operation and describes an <code>Evaluation</code>.</p>
4#[non_exhaustive]
5#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::fmt::Debug)]
6pub struct GetEvaluationOutput {
7    /// <p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>
8    pub evaluation_id: ::std::option::Option<::std::string::String>,
9    /// <p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>
10    pub ml_model_id: ::std::option::Option<::std::string::String>,
11    /// <p>The <code>DataSource</code> used for this evaluation.</p>
12    pub evaluation_data_source_id: ::std::option::Option<::std::string::String>,
13    /// <p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>
14    pub input_data_location_s3: ::std::option::Option<::std::string::String>,
15    /// <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>
16    pub created_by_iam_user: ::std::option::Option<::std::string::String>,
17    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
18    pub created_at: ::std::option::Option<::aws_smithy_types::DateTime>,
19    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
20    pub last_updated_at: ::std::option::Option<::aws_smithy_types::DateTime>,
21    /// <p>A user-supplied name or description of the <code>Evaluation</code>.</p>
22    pub name: ::std::option::Option<::std::string::String>,
23    /// <p>The status of the evaluation. This element can have one of the following values:</p>
24    /// <ul>
25    /// <li>
26    /// <p><code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p></li>
27    /// <li>
28    /// <p><code>INPROGRESS</code> - The evaluation is underway.</p></li>
29    /// <li>
30    /// <p><code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p></li>
31    /// <li>
32    /// <p><code>COMPLETED</code> - The evaluation process completed successfully.</p></li>
33    /// <li>
34    /// <p><code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p></li>
35    /// </ul>
36    pub status: ::std::option::Option<crate::types::EntityStatus>,
37    /// <p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>:</p>
38    /// <ul>
39    /// <li>
40    /// <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance.</p></li>
41    /// <li>
42    /// <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>
43    /// <li>
44    /// <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance.</p></li>
45    /// </ul>
46    /// <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>
47    pub performance_metrics: ::std::option::Option<crate::types::PerformanceMetrics>,
48    /// <p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>
49    pub log_uri: ::std::option::Option<::std::string::String>,
50    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
51    pub message: ::std::option::Option<::std::string::String>,
52    /// <p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>
53    pub compute_time: ::std::option::Option<i64>,
54    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>
55    pub finished_at: ::std::option::Option<::aws_smithy_types::DateTime>,
56    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>
57    pub started_at: ::std::option::Option<::aws_smithy_types::DateTime>,
58    _request_id: Option<String>,
59}
60impl GetEvaluationOutput {
61    /// <p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>
62    pub fn evaluation_id(&self) -> ::std::option::Option<&str> {
63        self.evaluation_id.as_deref()
64    }
65    /// <p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>
66    pub fn ml_model_id(&self) -> ::std::option::Option<&str> {
67        self.ml_model_id.as_deref()
68    }
69    /// <p>The <code>DataSource</code> used for this evaluation.</p>
70    pub fn evaluation_data_source_id(&self) -> ::std::option::Option<&str> {
71        self.evaluation_data_source_id.as_deref()
72    }
73    /// <p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>
74    pub fn input_data_location_s3(&self) -> ::std::option::Option<&str> {
75        self.input_data_location_s3.as_deref()
76    }
77    /// <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>
78    pub fn created_by_iam_user(&self) -> ::std::option::Option<&str> {
79        self.created_by_iam_user.as_deref()
80    }
81    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
82    pub fn created_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
83        self.created_at.as_ref()
84    }
85    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
86    pub fn last_updated_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
87        self.last_updated_at.as_ref()
88    }
89    /// <p>A user-supplied name or description of the <code>Evaluation</code>.</p>
90    pub fn name(&self) -> ::std::option::Option<&str> {
91        self.name.as_deref()
92    }
93    /// <p>The status of the evaluation. This element can have one of the following values:</p>
94    /// <ul>
95    /// <li>
96    /// <p><code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p></li>
97    /// <li>
98    /// <p><code>INPROGRESS</code> - The evaluation is underway.</p></li>
99    /// <li>
100    /// <p><code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p></li>
101    /// <li>
102    /// <p><code>COMPLETED</code> - The evaluation process completed successfully.</p></li>
103    /// <li>
104    /// <p><code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p></li>
105    /// </ul>
106    pub fn status(&self) -> ::std::option::Option<&crate::types::EntityStatus> {
107        self.status.as_ref()
108    }
109    /// <p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>:</p>
110    /// <ul>
111    /// <li>
112    /// <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance.</p></li>
113    /// <li>
114    /// <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>
115    /// <li>
116    /// <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance.</p></li>
117    /// </ul>
118    /// <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>
119    pub fn performance_metrics(&self) -> ::std::option::Option<&crate::types::PerformanceMetrics> {
120        self.performance_metrics.as_ref()
121    }
122    /// <p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>
123    pub fn log_uri(&self) -> ::std::option::Option<&str> {
124        self.log_uri.as_deref()
125    }
126    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
127    pub fn message(&self) -> ::std::option::Option<&str> {
128        self.message.as_deref()
129    }
130    /// <p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>
131    pub fn compute_time(&self) -> ::std::option::Option<i64> {
132        self.compute_time
133    }
134    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>
135    pub fn finished_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
136        self.finished_at.as_ref()
137    }
138    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>
139    pub fn started_at(&self) -> ::std::option::Option<&::aws_smithy_types::DateTime> {
140        self.started_at.as_ref()
141    }
142}
143impl ::aws_types::request_id::RequestId for GetEvaluationOutput {
144    fn request_id(&self) -> Option<&str> {
145        self._request_id.as_deref()
146    }
147}
148impl GetEvaluationOutput {
149    /// Creates a new builder-style object to manufacture [`GetEvaluationOutput`](crate::operation::get_evaluation::GetEvaluationOutput).
150    pub fn builder() -> crate::operation::get_evaluation::builders::GetEvaluationOutputBuilder {
151        crate::operation::get_evaluation::builders::GetEvaluationOutputBuilder::default()
152    }
153}
154
155/// A builder for [`GetEvaluationOutput`](crate::operation::get_evaluation::GetEvaluationOutput).
156#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default, ::std::fmt::Debug)]
157#[non_exhaustive]
158pub struct GetEvaluationOutputBuilder {
159    pub(crate) evaluation_id: ::std::option::Option<::std::string::String>,
160    pub(crate) ml_model_id: ::std::option::Option<::std::string::String>,
161    pub(crate) evaluation_data_source_id: ::std::option::Option<::std::string::String>,
162    pub(crate) input_data_location_s3: ::std::option::Option<::std::string::String>,
163    pub(crate) created_by_iam_user: ::std::option::Option<::std::string::String>,
164    pub(crate) created_at: ::std::option::Option<::aws_smithy_types::DateTime>,
165    pub(crate) last_updated_at: ::std::option::Option<::aws_smithy_types::DateTime>,
166    pub(crate) name: ::std::option::Option<::std::string::String>,
167    pub(crate) status: ::std::option::Option<crate::types::EntityStatus>,
168    pub(crate) performance_metrics: ::std::option::Option<crate::types::PerformanceMetrics>,
169    pub(crate) log_uri: ::std::option::Option<::std::string::String>,
170    pub(crate) message: ::std::option::Option<::std::string::String>,
171    pub(crate) compute_time: ::std::option::Option<i64>,
172    pub(crate) finished_at: ::std::option::Option<::aws_smithy_types::DateTime>,
173    pub(crate) started_at: ::std::option::Option<::aws_smithy_types::DateTime>,
174    _request_id: Option<String>,
175}
176impl GetEvaluationOutputBuilder {
177    /// <p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>
178    pub fn evaluation_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
179        self.evaluation_id = ::std::option::Option::Some(input.into());
180        self
181    }
182    /// <p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>
183    pub fn set_evaluation_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
184        self.evaluation_id = input;
185        self
186    }
187    /// <p>The evaluation ID which is same as the <code>EvaluationId</code> in the request.</p>
188    pub fn get_evaluation_id(&self) -> &::std::option::Option<::std::string::String> {
189        &self.evaluation_id
190    }
191    /// <p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>
192    pub fn ml_model_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
193        self.ml_model_id = ::std::option::Option::Some(input.into());
194        self
195    }
196    /// <p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>
197    pub fn set_ml_model_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
198        self.ml_model_id = input;
199        self
200    }
201    /// <p>The ID of the <code>MLModel</code> that was the focus of the evaluation.</p>
202    pub fn get_ml_model_id(&self) -> &::std::option::Option<::std::string::String> {
203        &self.ml_model_id
204    }
205    /// <p>The <code>DataSource</code> used for this evaluation.</p>
206    pub fn evaluation_data_source_id(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
207        self.evaluation_data_source_id = ::std::option::Option::Some(input.into());
208        self
209    }
210    /// <p>The <code>DataSource</code> used for this evaluation.</p>
211    pub fn set_evaluation_data_source_id(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
212        self.evaluation_data_source_id = input;
213        self
214    }
215    /// <p>The <code>DataSource</code> used for this evaluation.</p>
216    pub fn get_evaluation_data_source_id(&self) -> &::std::option::Option<::std::string::String> {
217        &self.evaluation_data_source_id
218    }
219    /// <p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>
220    pub fn input_data_location_s3(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
221        self.input_data_location_s3 = ::std::option::Option::Some(input.into());
222        self
223    }
224    /// <p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>
225    pub fn set_input_data_location_s3(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
226        self.input_data_location_s3 = input;
227        self
228    }
229    /// <p>The location of the data file or directory in Amazon Simple Storage Service (Amazon S3).</p>
230    pub fn get_input_data_location_s3(&self) -> &::std::option::Option<::std::string::String> {
231        &self.input_data_location_s3
232    }
233    /// <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>
234    pub fn created_by_iam_user(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
235        self.created_by_iam_user = ::std::option::Option::Some(input.into());
236        self
237    }
238    /// <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>
239    pub fn set_created_by_iam_user(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
240        self.created_by_iam_user = input;
241        self
242    }
243    /// <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>
244    pub fn get_created_by_iam_user(&self) -> &::std::option::Option<::std::string::String> {
245        &self.created_by_iam_user
246    }
247    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
248    pub fn created_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
249        self.created_at = ::std::option::Option::Some(input);
250        self
251    }
252    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
253    pub fn set_created_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
254        self.created_at = input;
255        self
256    }
257    /// <p>The time that the <code>Evaluation</code> was created. The time is expressed in epoch time.</p>
258    pub fn get_created_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
259        &self.created_at
260    }
261    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
262    pub fn last_updated_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
263        self.last_updated_at = ::std::option::Option::Some(input);
264        self
265    }
266    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
267    pub fn set_last_updated_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
268        self.last_updated_at = input;
269        self
270    }
271    /// <p>The time of the most recent edit to the <code>Evaluation</code>. The time is expressed in epoch time.</p>
272    pub fn get_last_updated_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
273        &self.last_updated_at
274    }
275    /// <p>A user-supplied name or description of the <code>Evaluation</code>.</p>
276    pub fn name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
277        self.name = ::std::option::Option::Some(input.into());
278        self
279    }
280    /// <p>A user-supplied name or description of the <code>Evaluation</code>.</p>
281    pub fn set_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
282        self.name = input;
283        self
284    }
285    /// <p>A user-supplied name or description of the <code>Evaluation</code>.</p>
286    pub fn get_name(&self) -> &::std::option::Option<::std::string::String> {
287        &self.name
288    }
289    /// <p>The status of the evaluation. This element can have one of the following values:</p>
290    /// <ul>
291    /// <li>
292    /// <p><code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p></li>
293    /// <li>
294    /// <p><code>INPROGRESS</code> - The evaluation is underway.</p></li>
295    /// <li>
296    /// <p><code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p></li>
297    /// <li>
298    /// <p><code>COMPLETED</code> - The evaluation process completed successfully.</p></li>
299    /// <li>
300    /// <p><code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p></li>
301    /// </ul>
302    pub fn status(mut self, input: crate::types::EntityStatus) -> Self {
303        self.status = ::std::option::Option::Some(input);
304        self
305    }
306    /// <p>The status of the evaluation. This element can have one of the following values:</p>
307    /// <ul>
308    /// <li>
309    /// <p><code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p></li>
310    /// <li>
311    /// <p><code>INPROGRESS</code> - The evaluation is underway.</p></li>
312    /// <li>
313    /// <p><code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p></li>
314    /// <li>
315    /// <p><code>COMPLETED</code> - The evaluation process completed successfully.</p></li>
316    /// <li>
317    /// <p><code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p></li>
318    /// </ul>
319    pub fn set_status(mut self, input: ::std::option::Option<crate::types::EntityStatus>) -> Self {
320        self.status = input;
321        self
322    }
323    /// <p>The status of the evaluation. This element can have one of the following values:</p>
324    /// <ul>
325    /// <li>
326    /// <p><code>PENDING</code> - Amazon Machine Language (Amazon ML) submitted a request to evaluate an <code>MLModel</code>.</p></li>
327    /// <li>
328    /// <p><code>INPROGRESS</code> - The evaluation is underway.</p></li>
329    /// <li>
330    /// <p><code>FAILED</code> - The request to evaluate an <code>MLModel</code> did not run to completion. It is not usable.</p></li>
331    /// <li>
332    /// <p><code>COMPLETED</code> - The evaluation process completed successfully.</p></li>
333    /// <li>
334    /// <p><code>DELETED</code> - The <code>Evaluation</code> is marked as deleted. It is not usable.</p></li>
335    /// </ul>
336    pub fn get_status(&self) -> &::std::option::Option<crate::types::EntityStatus> {
337        &self.status
338    }
339    /// <p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>:</p>
340    /// <ul>
341    /// <li>
342    /// <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance.</p></li>
343    /// <li>
344    /// <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>
345    /// <li>
346    /// <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance.</p></li>
347    /// </ul>
348    /// <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>
349    pub fn performance_metrics(mut self, input: crate::types::PerformanceMetrics) -> Self {
350        self.performance_metrics = ::std::option::Option::Some(input);
351        self
352    }
353    /// <p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>:</p>
354    /// <ul>
355    /// <li>
356    /// <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance.</p></li>
357    /// <li>
358    /// <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>
359    /// <li>
360    /// <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance.</p></li>
361    /// </ul>
362    /// <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>
363    pub fn set_performance_metrics(mut self, input: ::std::option::Option<crate::types::PerformanceMetrics>) -> Self {
364        self.performance_metrics = input;
365        self
366    }
367    /// <p>Measurements of how well the <code>MLModel</code> performed using observations referenced by the <code>DataSource</code>. One of the following metric is returned based on the type of the <code>MLModel</code>:</p>
368    /// <ul>
369    /// <li>
370    /// <p>BinaryAUC: A binary <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure performance.</p></li>
371    /// <li>
372    /// <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>
373    /// <li>
374    /// <p>MulticlassAvgFScore: A multiclass <code>MLModel</code> uses the F1 score technique to measure performance.</p></li>
375    /// </ul>
376    /// <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>
377    pub fn get_performance_metrics(&self) -> &::std::option::Option<crate::types::PerformanceMetrics> {
378        &self.performance_metrics
379    }
380    /// <p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>
381    pub fn log_uri(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
382        self.log_uri = ::std::option::Option::Some(input.into());
383        self
384    }
385    /// <p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>
386    pub fn set_log_uri(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
387        self.log_uri = input;
388        self
389    }
390    /// <p>A link to the file that contains logs of the <code>CreateEvaluation</code> operation.</p>
391    pub fn get_log_uri(&self) -> &::std::option::Option<::std::string::String> {
392        &self.log_uri
393    }
394    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
395    pub fn message(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
396        self.message = ::std::option::Option::Some(input.into());
397        self
398    }
399    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
400    pub fn set_message(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
401        self.message = input;
402        self
403    }
404    /// <p>A description of the most recent details about evaluating the <code>MLModel</code>.</p>
405    pub fn get_message(&self) -> &::std::option::Option<::std::string::String> {
406        &self.message
407    }
408    /// <p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>
409    pub fn compute_time(mut self, input: i64) -> Self {
410        self.compute_time = ::std::option::Option::Some(input);
411        self
412    }
413    /// <p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>
414    pub fn set_compute_time(mut self, input: ::std::option::Option<i64>) -> Self {
415        self.compute_time = input;
416        self
417    }
418    /// <p>The approximate CPU time in milliseconds that Amazon Machine Learning spent processing the <code>Evaluation</code>, normalized and scaled on computation resources. <code>ComputeTime</code> is only available if the <code>Evaluation</code> is in the <code>COMPLETED</code> state.</p>
419    pub fn get_compute_time(&self) -> &::std::option::Option<i64> {
420        &self.compute_time
421    }
422    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>
423    pub fn finished_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
424        self.finished_at = ::std::option::Option::Some(input);
425        self
426    }
427    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>
428    pub fn set_finished_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
429        self.finished_at = input;
430        self
431    }
432    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>COMPLETED</code> or <code>FAILED</code>. <code>FinishedAt</code> is only available when the <code>Evaluation</code> is in the <code>COMPLETED</code> or <code>FAILED</code> state.</p>
433    pub fn get_finished_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
434        &self.finished_at
435    }
436    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>
437    pub fn started_at(mut self, input: ::aws_smithy_types::DateTime) -> Self {
438        self.started_at = ::std::option::Option::Some(input);
439        self
440    }
441    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>
442    pub fn set_started_at(mut self, input: ::std::option::Option<::aws_smithy_types::DateTime>) -> Self {
443        self.started_at = input;
444        self
445    }
446    /// <p>The epoch time when Amazon Machine Learning marked the <code>Evaluation</code> as <code>INPROGRESS</code>. <code>StartedAt</code> isn't available if the <code>Evaluation</code> is in the <code>PENDING</code> state.</p>
447    pub fn get_started_at(&self) -> &::std::option::Option<::aws_smithy_types::DateTime> {
448        &self.started_at
449    }
450    pub(crate) fn _request_id(mut self, request_id: impl Into<String>) -> Self {
451        self._request_id = Some(request_id.into());
452        self
453    }
454
455    pub(crate) fn _set_request_id(&mut self, request_id: Option<String>) -> &mut Self {
456        self._request_id = request_id;
457        self
458    }
459    /// Consumes the builder and constructs a [`GetEvaluationOutput`](crate::operation::get_evaluation::GetEvaluationOutput).
460    pub fn build(self) -> crate::operation::get_evaluation::GetEvaluationOutput {
461        crate::operation::get_evaluation::GetEvaluationOutput {
462            evaluation_id: self.evaluation_id,
463            ml_model_id: self.ml_model_id,
464            evaluation_data_source_id: self.evaluation_data_source_id,
465            input_data_location_s3: self.input_data_location_s3,
466            created_by_iam_user: self.created_by_iam_user,
467            created_at: self.created_at,
468            last_updated_at: self.last_updated_at,
469            name: self.name,
470            status: self.status,
471            performance_metrics: self.performance_metrics,
472            log_uri: self.log_uri,
473            message: self.message,
474            compute_time: self.compute_time,
475            finished_at: self.finished_at,
476            started_at: self.started_at,
477            _request_id: self._request_id,
478        }
479    }
480}