1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_transform_job::_create_transform_job_output::CreateTransformJobOutputBuilder;

pub use crate::operation::create_transform_job::_create_transform_job_input::CreateTransformJobInputBuilder;

impl crate::operation::create_transform_job::builders::CreateTransformJobInputBuilder {
    /// Sends a request with this input using the given client.
    pub async fn send_with(
        self,
        client: &crate::Client,
    ) -> ::std::result::Result<
        crate::operation::create_transform_job::CreateTransformJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_transform_job::CreateTransformJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let mut fluent_builder = client.create_transform_job();
        fluent_builder.inner = self;
        fluent_builder.send().await
    }
}
/// Fluent builder constructing a request to `CreateTransformJob`.
///
/// <p>Starts a transform job. A transform job uses a trained model to get inferences on a dataset and saves these results to an Amazon S3 location that you specify.</p>
/// <p>To perform batch transformations, you create a transform job and use the data that you have readily available.</p>
/// <p>In the request body, you provide the following:</p>
/// <ul>
/// <li>
/// <p><code>TransformJobName</code> - Identifies the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.</p></li>
/// <li>
/// <p><code>ModelName</code> - Identifies the model to use. <code>ModelName</code> must be the name of an existing Amazon SageMaker model in the same Amazon Web Services Region and Amazon Web Services account. For information on creating a model, see <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html">CreateModel</a>.</p></li>
/// <li>
/// <p><code>TransformInput</code> - Describes the dataset to be transformed and the Amazon S3 location where it is stored.</p></li>
/// <li>
/// <p><code>TransformOutput</code> - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results from the transform job.</p></li>
/// <li>
/// <p><code>TransformResources</code> - Identifies the ML compute instances for the transform job.</p></li>
/// </ul>
/// <p>For more information about how batch transformation works, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html">Batch Transform</a>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateTransformJobFluentBuilder {
    handle: ::std::sync::Arc<crate::client::Handle>,
    inner: crate::operation::create_transform_job::builders::CreateTransformJobInputBuilder,
    config_override: ::std::option::Option<crate::config::Builder>,
}
impl
    crate::client::customize::internal::CustomizableSend<
        crate::operation::create_transform_job::CreateTransformJobOutput,
        crate::operation::create_transform_job::CreateTransformJobError,
    > for CreateTransformJobFluentBuilder
{
    fn send(
        self,
        config_override: crate::config::Builder,
    ) -> crate::client::customize::internal::BoxFuture<
        crate::client::customize::internal::SendResult<
            crate::operation::create_transform_job::CreateTransformJobOutput,
            crate::operation::create_transform_job::CreateTransformJobError,
        >,
    > {
        ::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
    }
}
impl CreateTransformJobFluentBuilder {
    /// Creates a new `CreateTransformJobFluentBuilder`.
    pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
        Self {
            handle,
            inner: ::std::default::Default::default(),
            config_override: ::std::option::Option::None,
        }
    }
    /// Access the CreateTransformJob as a reference.
    pub fn as_input(&self) -> &crate::operation::create_transform_job::builders::CreateTransformJobInputBuilder {
        &self.inner
    }
    /// Sends the request and returns the response.
    ///
    /// If an error occurs, an `SdkError` will be returned with additional details that
    /// can be matched against.
    ///
    /// By default, any retryable failures will be retried twice. Retry behavior
    /// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
    /// set when configuring the client.
    pub async fn send(
        self,
    ) -> ::std::result::Result<
        crate::operation::create_transform_job::CreateTransformJobOutput,
        ::aws_smithy_runtime_api::client::result::SdkError<
            crate::operation::create_transform_job::CreateTransformJobError,
            ::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
        >,
    > {
        let input = self
            .inner
            .build()
            .map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
        let runtime_plugins = crate::operation::create_transform_job::CreateTransformJob::operation_runtime_plugins(
            self.handle.runtime_plugins.clone(),
            &self.handle.conf,
            self.config_override,
        );
        crate::operation::create_transform_job::CreateTransformJob::orchestrate(&runtime_plugins, input).await
    }

    /// Consumes this builder, creating a customizable operation that can be modified before being sent.
    pub fn customize(
        self,
    ) -> crate::client::customize::CustomizableOperation<
        crate::operation::create_transform_job::CreateTransformJobOutput,
        crate::operation::create_transform_job::CreateTransformJobError,
        Self,
    > {
        crate::client::customize::CustomizableOperation::new(self)
    }
    pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
        self.set_config_override(::std::option::Option::Some(config_override.into()));
        self
    }

    pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
        self.config_override = config_override;
        self
    }
    /// <p>The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn transform_job_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.transform_job_name(input.into());
        self
    }
    /// <p>The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn set_transform_job_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_transform_job_name(input);
        self
    }
    /// <p>The name of the transform job. The name must be unique within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn get_transform_job_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_transform_job_name()
    }
    /// <p>The name of the model that you want to use for the transform job. <code>ModelName</code> must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn model_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.model_name(input.into());
        self
    }
    /// <p>The name of the model that you want to use for the transform job. <code>ModelName</code> must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn set_model_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
        self.inner = self.inner.set_model_name(input);
        self
    }
    /// <p>The name of the model that you want to use for the transform job. <code>ModelName</code> must be the name of an existing Amazon SageMaker model within an Amazon Web Services Region in an Amazon Web Services account.</p>
    pub fn get_model_name(&self) -> &::std::option::Option<::std::string::String> {
        self.inner.get_model_name()
    }
    /// <p>The maximum number of parallel requests that can be sent to each instance in a transform job. If <code>MaxConcurrentTransforms</code> is set to <code>0</code> or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is <code>1</code>. For more information on execution-parameters, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests">How Containers Serve Requests</a>. For built-in algorithms, you don't need to set a value for <code>MaxConcurrentTransforms</code>.</p>
    pub fn max_concurrent_transforms(mut self, input: i32) -> Self {
        self.inner = self.inner.max_concurrent_transforms(input);
        self
    }
    /// <p>The maximum number of parallel requests that can be sent to each instance in a transform job. If <code>MaxConcurrentTransforms</code> is set to <code>0</code> or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is <code>1</code>. For more information on execution-parameters, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests">How Containers Serve Requests</a>. For built-in algorithms, you don't need to set a value for <code>MaxConcurrentTransforms</code>.</p>
    pub fn set_max_concurrent_transforms(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_max_concurrent_transforms(input);
        self
    }
    /// <p>The maximum number of parallel requests that can be sent to each instance in a transform job. If <code>MaxConcurrentTransforms</code> is set to <code>0</code> or left unset, Amazon SageMaker checks the optional execution-parameters to determine the settings for your chosen algorithm. If the execution-parameters endpoint is not enabled, the default value is <code>1</code>. For more information on execution-parameters, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests">How Containers Serve Requests</a>. For built-in algorithms, you don't need to set a value for <code>MaxConcurrentTransforms</code>.</p>
    pub fn get_max_concurrent_transforms(&self) -> &::std::option::Option<i32> {
        self.inner.get_max_concurrent_transforms()
    }
    /// <p>Configures the timeout and maximum number of retries for processing a transform job invocation.</p>
    pub fn model_client_config(mut self, input: crate::types::ModelClientConfig) -> Self {
        self.inner = self.inner.model_client_config(input);
        self
    }
    /// <p>Configures the timeout and maximum number of retries for processing a transform job invocation.</p>
    pub fn set_model_client_config(mut self, input: ::std::option::Option<crate::types::ModelClientConfig>) -> Self {
        self.inner = self.inner.set_model_client_config(input);
        self
    }
    /// <p>Configures the timeout and maximum number of retries for processing a transform job invocation.</p>
    pub fn get_model_client_config(&self) -> &::std::option::Option<crate::types::ModelClientConfig> {
        self.inner.get_model_client_config()
    }
    /// <p>The maximum allowed size of the payload, in MB. A <i>payload</i> is the data portion of a record (without metadata). The value in <code>MaxPayloadInMB</code> must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is <code>6</code> MB.</p>
    /// <p>The value of <code>MaxPayloadInMB</code> cannot be greater than 100 MB. If you specify the <code>MaxConcurrentTransforms</code> parameter, the value of <code>(MaxConcurrentTransforms * MaxPayloadInMB)</code> also cannot exceed 100 MB.</p>
    /// <p>For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to <code>0</code>. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.</p>
    pub fn max_payload_in_mb(mut self, input: i32) -> Self {
        self.inner = self.inner.max_payload_in_mb(input);
        self
    }
    /// <p>The maximum allowed size of the payload, in MB. A <i>payload</i> is the data portion of a record (without metadata). The value in <code>MaxPayloadInMB</code> must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is <code>6</code> MB.</p>
    /// <p>The value of <code>MaxPayloadInMB</code> cannot be greater than 100 MB. If you specify the <code>MaxConcurrentTransforms</code> parameter, the value of <code>(MaxConcurrentTransforms * MaxPayloadInMB)</code> also cannot exceed 100 MB.</p>
    /// <p>For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to <code>0</code>. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.</p>
    pub fn set_max_payload_in_mb(mut self, input: ::std::option::Option<i32>) -> Self {
        self.inner = self.inner.set_max_payload_in_mb(input);
        self
    }
    /// <p>The maximum allowed size of the payload, in MB. A <i>payload</i> is the data portion of a record (without metadata). The value in <code>MaxPayloadInMB</code> must be greater than, or equal to, the size of a single record. To estimate the size of a record in MB, divide the size of your dataset by the number of records. To ensure that the records fit within the maximum payload size, we recommend using a slightly larger value. The default value is <code>6</code> MB.</p>
    /// <p>The value of <code>MaxPayloadInMB</code> cannot be greater than 100 MB. If you specify the <code>MaxConcurrentTransforms</code> parameter, the value of <code>(MaxConcurrentTransforms * MaxPayloadInMB)</code> also cannot exceed 100 MB.</p>
    /// <p>For cases where the payload might be arbitrarily large and is transmitted using HTTP chunked encoding, set the value to <code>0</code>. This feature works only in supported algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP chunked encoding.</p>
    pub fn get_max_payload_in_mb(&self) -> &::std::option::Option<i32> {
        self.inner.get_max_payload_in_mb()
    }
    /// <p>Specifies the number of records to include in a mini-batch for an HTTP inference request. A <i>record</i> <i></i> is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.</p>
    /// <p>To enable the batch strategy, you must set the <code>SplitType</code> property to <code>Line</code>, <code>RecordIO</code>, or <code>TFRecord</code>.</p>
    /// <p>To use only one record when making an HTTP invocation request to a container, set <code>BatchStrategy</code> to <code>SingleRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    /// <p>To fit as many records in a mini-batch as can fit within the <code>MaxPayloadInMB</code> limit, set <code>BatchStrategy</code> to <code>MultiRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    pub fn batch_strategy(mut self, input: crate::types::BatchStrategy) -> Self {
        self.inner = self.inner.batch_strategy(input);
        self
    }
    /// <p>Specifies the number of records to include in a mini-batch for an HTTP inference request. A <i>record</i> <i></i> is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.</p>
    /// <p>To enable the batch strategy, you must set the <code>SplitType</code> property to <code>Line</code>, <code>RecordIO</code>, or <code>TFRecord</code>.</p>
    /// <p>To use only one record when making an HTTP invocation request to a container, set <code>BatchStrategy</code> to <code>SingleRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    /// <p>To fit as many records in a mini-batch as can fit within the <code>MaxPayloadInMB</code> limit, set <code>BatchStrategy</code> to <code>MultiRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    pub fn set_batch_strategy(mut self, input: ::std::option::Option<crate::types::BatchStrategy>) -> Self {
        self.inner = self.inner.set_batch_strategy(input);
        self
    }
    /// <p>Specifies the number of records to include in a mini-batch for an HTTP inference request. A <i>record</i> <i></i> is a single unit of input data that inference can be made on. For example, a single line in a CSV file is a record.</p>
    /// <p>To enable the batch strategy, you must set the <code>SplitType</code> property to <code>Line</code>, <code>RecordIO</code>, or <code>TFRecord</code>.</p>
    /// <p>To use only one record when making an HTTP invocation request to a container, set <code>BatchStrategy</code> to <code>SingleRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    /// <p>To fit as many records in a mini-batch as can fit within the <code>MaxPayloadInMB</code> limit, set <code>BatchStrategy</code> to <code>MultiRecord</code> and <code>SplitType</code> to <code>Line</code>.</p>
    pub fn get_batch_strategy(&self) -> &::std::option::Option<crate::types::BatchStrategy> {
        self.inner.get_batch_strategy()
    }
    ///
    /// Adds a key-value pair to `Environment`.
    ///
    /// To override the contents of this collection use [`set_environment`](Self::set_environment).
    ///
    /// <p>The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.</p>
    pub fn environment(mut self, k: impl ::std::convert::Into<::std::string::String>, v: impl ::std::convert::Into<::std::string::String>) -> Self {
        self.inner = self.inner.environment(k.into(), v.into());
        self
    }
    /// <p>The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.</p>
    pub fn set_environment(
        mut self,
        input: ::std::option::Option<::std::collections::HashMap<::std::string::String, ::std::string::String>>,
    ) -> Self {
        self.inner = self.inner.set_environment(input);
        self
    }
    /// <p>The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.</p>
    pub fn get_environment(&self) -> &::std::option::Option<::std::collections::HashMap<::std::string::String, ::std::string::String>> {
        self.inner.get_environment()
    }
    /// <p>Describes the input source and the way the transform job consumes it.</p>
    pub fn transform_input(mut self, input: crate::types::TransformInput) -> Self {
        self.inner = self.inner.transform_input(input);
        self
    }
    /// <p>Describes the input source and the way the transform job consumes it.</p>
    pub fn set_transform_input(mut self, input: ::std::option::Option<crate::types::TransformInput>) -> Self {
        self.inner = self.inner.set_transform_input(input);
        self
    }
    /// <p>Describes the input source and the way the transform job consumes it.</p>
    pub fn get_transform_input(&self) -> &::std::option::Option<crate::types::TransformInput> {
        self.inner.get_transform_input()
    }
    /// <p>Describes the results of the transform job.</p>
    pub fn transform_output(mut self, input: crate::types::TransformOutput) -> Self {
        self.inner = self.inner.transform_output(input);
        self
    }
    /// <p>Describes the results of the transform job.</p>
    pub fn set_transform_output(mut self, input: ::std::option::Option<crate::types::TransformOutput>) -> Self {
        self.inner = self.inner.set_transform_output(input);
        self
    }
    /// <p>Describes the results of the transform job.</p>
    pub fn get_transform_output(&self) -> &::std::option::Option<crate::types::TransformOutput> {
        self.inner.get_transform_output()
    }
    /// <p>Configuration to control how SageMaker captures inference data.</p>
    pub fn data_capture_config(mut self, input: crate::types::BatchDataCaptureConfig) -> Self {
        self.inner = self.inner.data_capture_config(input);
        self
    }
    /// <p>Configuration to control how SageMaker captures inference data.</p>
    pub fn set_data_capture_config(mut self, input: ::std::option::Option<crate::types::BatchDataCaptureConfig>) -> Self {
        self.inner = self.inner.set_data_capture_config(input);
        self
    }
    /// <p>Configuration to control how SageMaker captures inference data.</p>
    pub fn get_data_capture_config(&self) -> &::std::option::Option<crate::types::BatchDataCaptureConfig> {
        self.inner.get_data_capture_config()
    }
    /// <p>Describes the resources, including ML instance types and ML instance count, to use for the transform job.</p>
    pub fn transform_resources(mut self, input: crate::types::TransformResources) -> Self {
        self.inner = self.inner.transform_resources(input);
        self
    }
    /// <p>Describes the resources, including ML instance types and ML instance count, to use for the transform job.</p>
    pub fn set_transform_resources(mut self, input: ::std::option::Option<crate::types::TransformResources>) -> Self {
        self.inner = self.inner.set_transform_resources(input);
        self
    }
    /// <p>Describes the resources, including ML instance types and ML instance count, to use for the transform job.</p>
    pub fn get_transform_resources(&self) -> &::std::option::Option<crate::types::TransformResources> {
        self.inner.get_transform_resources()
    }
    /// <p>The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html">Associate Prediction Results with their Corresponding Input Records</a>.</p>
    pub fn data_processing(mut self, input: crate::types::DataProcessing) -> Self {
        self.inner = self.inner.data_processing(input);
        self
    }
    /// <p>The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html">Associate Prediction Results with their Corresponding Input Records</a>.</p>
    pub fn set_data_processing(mut self, input: ::std::option::Option<crate::types::DataProcessing>) -> Self {
        self.inner = self.inner.set_data_processing(input);
        self
    }
    /// <p>The data structure used to specify the data to be used for inference in a batch transform job and to associate the data that is relevant to the prediction results in the output. The input filter provided allows you to exclude input data that is not needed for inference in a batch transform job. The output filter provided allows you to include input data relevant to interpreting the predictions in the output from the job. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html">Associate Prediction Results with their Corresponding Input Records</a>.</p>
    pub fn get_data_processing(&self) -> &::std::option::Option<crate::types::DataProcessing> {
        self.inner.get_data_processing()
    }
    ///
    /// Appends an item to `Tags`.
    ///
    /// To override the contents of this collection use [`set_tags`](Self::set_tags).
    ///
    /// <p>(Optional) An array of key-value pairs. For more information, see <a href="https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what">Using Cost Allocation Tags</a> in the <i>Amazon Web Services Billing and Cost Management User Guide</i>.</p>
    pub fn tags(mut self, input: crate::types::Tag) -> Self {
        self.inner = self.inner.tags(input);
        self
    }
    /// <p>(Optional) An array of key-value pairs. For more information, see <a href="https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what">Using Cost Allocation Tags</a> in the <i>Amazon Web Services Billing and Cost Management User Guide</i>.</p>
    pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
        self.inner = self.inner.set_tags(input);
        self
    }
    /// <p>(Optional) An array of key-value pairs. For more information, see <a href="https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what">Using Cost Allocation Tags</a> in the <i>Amazon Web Services Billing and Cost Management User Guide</i>.</p>
    pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
        self.inner.get_tags()
    }
    /// <p>Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:</p>
    /// <ul>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html">CreateProcessingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html">CreateTrainingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html">CreateTransformJob</a></p></li>
    /// </ul>
    pub fn experiment_config(mut self, input: crate::types::ExperimentConfig) -> Self {
        self.inner = self.inner.experiment_config(input);
        self
    }
    /// <p>Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:</p>
    /// <ul>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html">CreateProcessingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html">CreateTrainingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html">CreateTransformJob</a></p></li>
    /// </ul>
    pub fn set_experiment_config(mut self, input: ::std::option::Option<crate::types::ExperimentConfig>) -> Self {
        self.inner = self.inner.set_experiment_config(input);
        self
    }
    /// <p>Associates a SageMaker job as a trial component with an experiment and trial. Specified when you call the following APIs:</p>
    /// <ul>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html">CreateProcessingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html">CreateTrainingJob</a></p></li>
    /// <li>
    /// <p><a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html">CreateTransformJob</a></p></li>
    /// </ul>
    pub fn get_experiment_config(&self) -> &::std::option::Option<crate::types::ExperimentConfig> {
        self.inner.get_experiment_config()
    }
}