#[non_exhaustive]pub struct CreateSolutionInputBuilder { /* private fields */ }
Expand description
A builder for CreateSolutionInput
.
Implementations§
Source§impl CreateSolutionInputBuilder
impl CreateSolutionInputBuilder
Sourcepub fn name(self, input: impl Into<String>) -> Self
pub fn name(self, input: impl Into<String>) -> Self
The name for the solution.
This field is required.Sourcepub fn perform_hpo(self, input: bool) -> Self
pub fn perform_hpo(self, input: bool) -> Self
Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false
.
When performing AutoML, this parameter is always true
and you should not set it to false
.
Sourcepub fn set_perform_hpo(self, input: Option<bool>) -> Self
pub fn set_perform_hpo(self, input: Option<bool>) -> Self
Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false
.
When performing AutoML, this parameter is always true
and you should not set it to false
.
Sourcepub fn get_perform_hpo(&self) -> &Option<bool>
pub fn get_perform_hpo(&self) -> &Option<bool>
Whether to perform hyperparameter optimization (HPO) on the specified or selected recipe. The default is false
.
When performing AutoML, this parameter is always true
and you should not set it to false
.
Sourcepub fn perform_auto_ml(self, input: bool) -> Self
pub fn perform_auto_ml(self, input: bool) -> Self
We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Choosing a recipe.
Whether to perform automated machine learning (AutoML). The default is false
. For this case, you must specify recipeArn
.
When set to true
, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn
. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.
Sourcepub fn set_perform_auto_ml(self, input: Option<bool>) -> Self
pub fn set_perform_auto_ml(self, input: Option<bool>) -> Self
We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Choosing a recipe.
Whether to perform automated machine learning (AutoML). The default is false
. For this case, you must specify recipeArn
.
When set to true
, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn
. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.
Sourcepub fn get_perform_auto_ml(&self) -> &Option<bool>
pub fn get_perform_auto_ml(&self) -> &Option<bool>
We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Choosing a recipe.
Whether to perform automated machine learning (AutoML). The default is false
. For this case, you must specify recipeArn
.
When set to true
, Amazon Personalize analyzes your training data and selects the optimal USER_PERSONALIZATION recipe and hyperparameters. In this case, you must omit recipeArn
. Amazon Personalize determines the optimal recipe by running tests with different values for the hyperparameters. AutoML lengthens the training process as compared to selecting a specific recipe.
Sourcepub fn perform_auto_training(self, input: bool) -> Self
pub fn perform_auto_training(self, input: bool) -> Self
Whether the solution uses automatic training to create new solution versions (trained models). The default is True
and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a schedulingExpression
in the AutoTrainingConfig
as part of solution configuration. For more information about automatic training, see Configuring automatic training.
Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.
After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion.
Sourcepub fn set_perform_auto_training(self, input: Option<bool>) -> Self
pub fn set_perform_auto_training(self, input: Option<bool>) -> Self
Whether the solution uses automatic training to create new solution versions (trained models). The default is True
and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a schedulingExpression
in the AutoTrainingConfig
as part of solution configuration. For more information about automatic training, see Configuring automatic training.
Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.
After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion.
Sourcepub fn get_perform_auto_training(&self) -> &Option<bool>
pub fn get_perform_auto_training(&self) -> &Option<bool>
Whether the solution uses automatic training to create new solution versions (trained models). The default is True
and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a schedulingExpression
in the AutoTrainingConfig
as part of solution configuration. For more information about automatic training, see Configuring automatic training.
Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.
After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion.
Sourcepub fn recipe_arn(self, input: impl Into<String>) -> Self
pub fn recipe_arn(self, input: impl Into<String>) -> Self
The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when performAutoML
is false. For information about different Amazon Personalize recipes and their ARNs, see Choosing a recipe.
Sourcepub fn set_recipe_arn(self, input: Option<String>) -> Self
pub fn set_recipe_arn(self, input: Option<String>) -> Self
The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when performAutoML
is false. For information about different Amazon Personalize recipes and their ARNs, see Choosing a recipe.
Sourcepub fn get_recipe_arn(&self) -> &Option<String>
pub fn get_recipe_arn(&self) -> &Option<String>
The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when performAutoML
is false. For information about different Amazon Personalize recipes and their ARNs, see Choosing a recipe.
Sourcepub fn dataset_group_arn(self, input: impl Into<String>) -> Self
pub fn dataset_group_arn(self, input: impl Into<String>) -> Self
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
This field is required.Sourcepub fn set_dataset_group_arn(self, input: Option<String>) -> Self
pub fn set_dataset_group_arn(self, input: Option<String>) -> Self
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
Sourcepub fn get_dataset_group_arn(&self) -> &Option<String>
pub fn get_dataset_group_arn(&self) -> &Option<String>
The Amazon Resource Name (ARN) of the dataset group that provides the training data.
Sourcepub fn event_type(self, input: impl Into<String>) -> Self
pub fn event_type(self, input: impl Into<String>) -> Self
When your have multiple event types (using an EVENT_TYPE
schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
If you do not provide an eventType
, Amazon Personalize will use all interactions for training with equal weight regardless of type.
Sourcepub fn set_event_type(self, input: Option<String>) -> Self
pub fn set_event_type(self, input: Option<String>) -> Self
When your have multiple event types (using an EVENT_TYPE
schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
If you do not provide an eventType
, Amazon Personalize will use all interactions for training with equal weight regardless of type.
Sourcepub fn get_event_type(&self) -> &Option<String>
pub fn get_event_type(&self) -> &Option<String>
When your have multiple event types (using an EVENT_TYPE
schema field), this parameter specifies which event type (for example, 'click' or 'like') is used for training the model.
If you do not provide an eventType
, Amazon Personalize will use all interactions for training with equal weight regardless of type.
Sourcepub fn solution_config(self, input: SolutionConfig) -> Self
pub fn solution_config(self, input: SolutionConfig) -> Self
The configuration properties for the solution. When performAutoML
is set to true, Amazon Personalize only evaluates the autoMLConfig
section of the solution configuration.
Amazon Personalize doesn't support configuring the hpoObjective
at this time.
Sourcepub fn set_solution_config(self, input: Option<SolutionConfig>) -> Self
pub fn set_solution_config(self, input: Option<SolutionConfig>) -> Self
The configuration properties for the solution. When performAutoML
is set to true, Amazon Personalize only evaluates the autoMLConfig
section of the solution configuration.
Amazon Personalize doesn't support configuring the hpoObjective
at this time.
Sourcepub fn get_solution_config(&self) -> &Option<SolutionConfig>
pub fn get_solution_config(&self) -> &Option<SolutionConfig>
The configuration properties for the solution. When performAutoML
is set to true, Amazon Personalize only evaluates the autoMLConfig
section of the solution configuration.
Amazon Personalize doesn't support configuring the hpoObjective
at this time.
A list of tags to apply to the solution.
A list of tags to apply to the solution.
Sourcepub fn build(self) -> Result<CreateSolutionInput, BuildError>
pub fn build(self) -> Result<CreateSolutionInput, BuildError>
Consumes the builder and constructs a CreateSolutionInput
.
Source§impl CreateSolutionInputBuilder
impl CreateSolutionInputBuilder
Sourcepub async fn send_with(
self,
client: &Client,
) -> Result<CreateSolutionOutput, SdkError<CreateSolutionError, HttpResponse>>
pub async fn send_with( self, client: &Client, ) -> Result<CreateSolutionOutput, SdkError<CreateSolutionError, HttpResponse>>
Sends a request with this input using the given client.
Trait Implementations§
Source§impl Clone for CreateSolutionInputBuilder
impl Clone for CreateSolutionInputBuilder
Source§fn clone(&self) -> CreateSolutionInputBuilder
fn clone(&self) -> CreateSolutionInputBuilder
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Debug for CreateSolutionInputBuilder
impl Debug for CreateSolutionInputBuilder
Source§impl Default for CreateSolutionInputBuilder
impl Default for CreateSolutionInputBuilder
Source§fn default() -> CreateSolutionInputBuilder
fn default() -> CreateSolutionInputBuilder
impl StructuralPartialEq for CreateSolutionInputBuilder
Auto Trait Implementations§
impl Freeze for CreateSolutionInputBuilder
impl RefUnwindSafe for CreateSolutionInputBuilder
impl Send for CreateSolutionInputBuilder
impl Sync for CreateSolutionInputBuilder
impl Unpin for CreateSolutionInputBuilder
impl UnwindSafe for CreateSolutionInputBuilder
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