aws_sdk_personalize/operation/update_solution/_update_solution_input.rs
1// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
2#[allow(missing_docs)] // documentation missing in model
3#[non_exhaustive]
4#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::fmt::Debug)]
5pub struct UpdateSolutionInput {
6 /// <p>The Amazon Resource Name (ARN) of the solution to update.</p>
7 pub solution_arn: ::std::option::Option<::std::string::String>,
8 /// <p>Whether the solution uses automatic training to create new solution versions (trained models). You can change the training frequency by specifying a <code>schedulingExpression</code> in the <code>AutoTrainingConfig</code> as part of solution configuration.</p>
9 /// <p>If you turn on automatic training, the first automatic training starts within one hour after the solution update completes. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information about automatic training, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html">Configuring automatic training</a>.</p>
10 /// <p>After training starts, you can get the solution version's Amazon Resource Name (ARN) with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> API operation. To get its status, use the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a>.</p>
11 pub perform_auto_training: ::std::option::Option<bool>,
12 /// <p>Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.</p>
13 pub perform_incremental_update: ::std::option::Option<bool>,
14 /// <p>The new configuration details of the solution.</p>
15 pub solution_update_config: ::std::option::Option<crate::types::SolutionUpdateConfig>,
16}
17impl UpdateSolutionInput {
18 /// <p>The Amazon Resource Name (ARN) of the solution to update.</p>
19 pub fn solution_arn(&self) -> ::std::option::Option<&str> {
20 self.solution_arn.as_deref()
21 }
22 /// <p>Whether the solution uses automatic training to create new solution versions (trained models). You can change the training frequency by specifying a <code>schedulingExpression</code> in the <code>AutoTrainingConfig</code> as part of solution configuration.</p>
23 /// <p>If you turn on automatic training, the first automatic training starts within one hour after the solution update completes. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information about automatic training, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html">Configuring automatic training</a>.</p>
24 /// <p>After training starts, you can get the solution version's Amazon Resource Name (ARN) with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> API operation. To get its status, use the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a>.</p>
25 pub fn perform_auto_training(&self) -> ::std::option::Option<bool> {
26 self.perform_auto_training
27 }
28 /// <p>Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.</p>
29 pub fn perform_incremental_update(&self) -> ::std::option::Option<bool> {
30 self.perform_incremental_update
31 }
32 /// <p>The new configuration details of the solution.</p>
33 pub fn solution_update_config(&self) -> ::std::option::Option<&crate::types::SolutionUpdateConfig> {
34 self.solution_update_config.as_ref()
35 }
36}
37impl UpdateSolutionInput {
38 /// Creates a new builder-style object to manufacture [`UpdateSolutionInput`](crate::operation::update_solution::UpdateSolutionInput).
39 pub fn builder() -> crate::operation::update_solution::builders::UpdateSolutionInputBuilder {
40 crate::operation::update_solution::builders::UpdateSolutionInputBuilder::default()
41 }
42}
43
44/// A builder for [`UpdateSolutionInput`](crate::operation::update_solution::UpdateSolutionInput).
45#[derive(::std::clone::Clone, ::std::cmp::PartialEq, ::std::default::Default, ::std::fmt::Debug)]
46#[non_exhaustive]
47pub struct UpdateSolutionInputBuilder {
48 pub(crate) solution_arn: ::std::option::Option<::std::string::String>,
49 pub(crate) perform_auto_training: ::std::option::Option<bool>,
50 pub(crate) perform_incremental_update: ::std::option::Option<bool>,
51 pub(crate) solution_update_config: ::std::option::Option<crate::types::SolutionUpdateConfig>,
52}
53impl UpdateSolutionInputBuilder {
54 /// <p>The Amazon Resource Name (ARN) of the solution to update.</p>
55 /// This field is required.
56 pub fn solution_arn(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
57 self.solution_arn = ::std::option::Option::Some(input.into());
58 self
59 }
60 /// <p>The Amazon Resource Name (ARN) of the solution to update.</p>
61 pub fn set_solution_arn(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
62 self.solution_arn = input;
63 self
64 }
65 /// <p>The Amazon Resource Name (ARN) of the solution to update.</p>
66 pub fn get_solution_arn(&self) -> &::std::option::Option<::std::string::String> {
67 &self.solution_arn
68 }
69 /// <p>Whether the solution uses automatic training to create new solution versions (trained models). You can change the training frequency by specifying a <code>schedulingExpression</code> in the <code>AutoTrainingConfig</code> as part of solution configuration.</p>
70 /// <p>If you turn on automatic training, the first automatic training starts within one hour after the solution update completes. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information about automatic training, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html">Configuring automatic training</a>.</p>
71 /// <p>After training starts, you can get the solution version's Amazon Resource Name (ARN) with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> API operation. To get its status, use the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a>.</p>
72 pub fn perform_auto_training(mut self, input: bool) -> Self {
73 self.perform_auto_training = ::std::option::Option::Some(input);
74 self
75 }
76 /// <p>Whether the solution uses automatic training to create new solution versions (trained models). You can change the training frequency by specifying a <code>schedulingExpression</code> in the <code>AutoTrainingConfig</code> as part of solution configuration.</p>
77 /// <p>If you turn on automatic training, the first automatic training starts within one hour after the solution update completes. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information about automatic training, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html">Configuring automatic training</a>.</p>
78 /// <p>After training starts, you can get the solution version's Amazon Resource Name (ARN) with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> API operation. To get its status, use the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a>.</p>
79 pub fn set_perform_auto_training(mut self, input: ::std::option::Option<bool>) -> Self {
80 self.perform_auto_training = input;
81 self
82 }
83 /// <p>Whether the solution uses automatic training to create new solution versions (trained models). You can change the training frequency by specifying a <code>schedulingExpression</code> in the <code>AutoTrainingConfig</code> as part of solution configuration.</p>
84 /// <p>If you turn on automatic training, the first automatic training starts within one hour after the solution update completes. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information about automatic training, see <a href="https://docs.aws.amazon.com/personalize/latest/dg/solution-config-auto-training.html">Configuring automatic training</a>.</p>
85 /// <p>After training starts, you can get the solution version's Amazon Resource Name (ARN) with the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_ListSolutionVersions.html">ListSolutionVersions</a> API operation. To get its status, use the <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_DescribeSolutionVersion.html">DescribeSolutionVersion</a>.</p>
86 pub fn get_perform_auto_training(&self) -> &::std::option::Option<bool> {
87 &self.perform_auto_training
88 }
89 /// <p>Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.</p>
90 pub fn perform_incremental_update(mut self, input: bool) -> Self {
91 self.perform_incremental_update = ::std::option::Option::Some(input);
92 self
93 }
94 /// <p>Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.</p>
95 pub fn set_perform_incremental_update(mut self, input: ::std::option::Option<bool>) -> Self {
96 self.perform_incremental_update = input;
97 self
98 }
99 /// <p>Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.</p>
100 pub fn get_perform_incremental_update(&self) -> &::std::option::Option<bool> {
101 &self.perform_incremental_update
102 }
103 /// <p>The new configuration details of the solution.</p>
104 pub fn solution_update_config(mut self, input: crate::types::SolutionUpdateConfig) -> Self {
105 self.solution_update_config = ::std::option::Option::Some(input);
106 self
107 }
108 /// <p>The new configuration details of the solution.</p>
109 pub fn set_solution_update_config(mut self, input: ::std::option::Option<crate::types::SolutionUpdateConfig>) -> Self {
110 self.solution_update_config = input;
111 self
112 }
113 /// <p>The new configuration details of the solution.</p>
114 pub fn get_solution_update_config(&self) -> &::std::option::Option<crate::types::SolutionUpdateConfig> {
115 &self.solution_update_config
116 }
117 /// Consumes the builder and constructs a [`UpdateSolutionInput`](crate::operation::update_solution::UpdateSolutionInput).
118 pub fn build(
119 self,
120 ) -> ::std::result::Result<crate::operation::update_solution::UpdateSolutionInput, ::aws_smithy_types::error::operation::BuildError> {
121 ::std::result::Result::Ok(crate::operation::update_solution::UpdateSolutionInput {
122 solution_arn: self.solution_arn,
123 perform_auto_training: self.perform_auto_training,
124 perform_incremental_update: self.perform_incremental_update,
125 solution_update_config: self.solution_update_config,
126 })
127 }
128}