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