Struct aws_sdk_personalize::operation::create_solution_version::builders::CreateSolutionVersionInputBuilder

#[non_exhaustive]
pub struct CreateSolutionVersionInputBuilder { /* private fields */ }

A builder for CreateSolutionVersionInput.

Implementations

impl CreateSolutionVersionInputBuilder

pub fn name(self, input: impl Into<String>) -> Self

The name of the solution version.

pub fn set_name(self, input: Option<String>) -> Self

The name of the solution version.

pub fn get_name(&self) -> &Option<String>

The name of the solution version.

pub fn solution_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the solution containing the training configuration information.

This field is required.

pub fn set_solution_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the solution containing the training configuration information.

pub fn get_solution_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of the solution containing the training configuration information.

pub fn training_mode(self, input: TrainingMode) -> Self

The scope of training to be performed when creating the solution version. The default is FULL. This creates a completely new model based on the entirety of the training data from the datasets in your dataset group.

If you use User-Personalization, you can specify a training mode of UPDATE. This updates the model to consider new items for recommendations. It is not a full retraining. You should still complete a full retraining weekly. If you specify UPDATE, Amazon Personalize will stop automatic updates for the solution version. To resume updates, create a new solution with training mode set to FULL and deploy it in a campaign. For more information about automatic updates, see Automatic updates.

The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the legacy HRNN-Coldstart recipe.

pub fn set_training_mode(self, input: Option<TrainingMode>) -> Self

The scope of training to be performed when creating the solution version. The default is FULL. This creates a completely new model based on the entirety of the training data from the datasets in your dataset group.

If you use User-Personalization, you can specify a training mode of UPDATE. This updates the model to consider new items for recommendations. It is not a full retraining. You should still complete a full retraining weekly. If you specify UPDATE, Amazon Personalize will stop automatic updates for the solution version. To resume updates, create a new solution with training mode set to FULL and deploy it in a campaign. For more information about automatic updates, see Automatic updates.

The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the legacy HRNN-Coldstart recipe.

pub fn get_training_mode(&self) -> &Option<TrainingMode>

The scope of training to be performed when creating the solution version. The default is FULL. This creates a completely new model based on the entirety of the training data from the datasets in your dataset group.

If you use User-Personalization, you can specify a training mode of UPDATE. This updates the model to consider new items for recommendations. It is not a full retraining. You should still complete a full retraining weekly. If you specify UPDATE, Amazon Personalize will stop automatic updates for the solution version. To resume updates, create a new solution with training mode set to FULL and deploy it in a campaign. For more information about automatic updates, see Automatic updates.

The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the legacy HRNN-Coldstart recipe.

pub fn tags(self, input: Tag) -> Self

Appends an item to tags.

To override the contents of this collection use set_tags.

A list of tags to apply to the solution version.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

A list of tags to apply to the solution version.

pub fn get_tags(&self) -> &Option<Vec<Tag>>

A list of tags to apply to the solution version.

pub fn build(self) -> Result<CreateSolutionVersionInput, BuildError>

Consumes the builder and constructs a CreateSolutionVersionInput.

impl CreateSolutionVersionInputBuilder

pub async fn send_with( self, client: &Client ) -> Result<CreateSolutionVersionOutput, SdkError<CreateSolutionVersionError, HttpResponse>>

Sends a request with this input using the given client.

Trait Implementations

impl Clone for CreateSolutionVersionInputBuilder

fn clone(&self) -> CreateSolutionVersionInputBuilder

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateSolutionVersionInputBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for CreateSolutionVersionInputBuilder

fn default() -> CreateSolutionVersionInputBuilder

Returns the “default value” for a type.

impl PartialEq for CreateSolutionVersionInputBuilder

fn eq(&self, other: &CreateSolutionVersionInputBuilder) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateSolutionVersionInputBuilder