#[non_exhaustive]
pub struct SolutionVersion {
Show 15 fields pub solution_version_arn: Option<String>, pub solution_arn: Option<String>, pub perform_hpo: bool, pub perform_auto_ml: bool, pub recipe_arn: Option<String>, pub event_type: Option<String>, pub dataset_group_arn: Option<String>, pub solution_config: Option<SolutionConfig>, pub training_hours: Option<f64>, pub training_mode: Option<TrainingMode>, pub tuned_hpo_params: Option<TunedHpoParams>, pub status: Option<String>, pub failure_reason: Option<String>, pub creation_date_time: Option<DateTime>, pub last_updated_date_time: Option<DateTime>,
}
Expand description

An object that provides information about a specific version of a Solution in a Custom dataset group.

Fields (Non-exhaustive)

This struct is marked as non-exhaustive
Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.
solution_version_arn: Option<String>

The ARN of the solution version.

solution_arn: Option<String>

The ARN of the solution.

perform_hpo: bool

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.

perform_auto_ml: bool

When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses recipeArn.

recipe_arn: Option<String>

The ARN of the recipe used in the solution.

event_type: Option<String>

The event type (for example, 'click' or 'like') that is used for training the model.

dataset_group_arn: Option<String>

The Amazon Resource Name (ARN) of the dataset group providing the training data.

solution_config: Option<SolutionConfig>

Describes the configuration properties for the solution.

training_hours: Option<f64>

The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.

training_mode: Option<TrainingMode>

The scope of training to be performed when creating the solution version. The FULL option trains the solution version based on the entirety of the input solution's training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

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 HRNN-Coldstart recipe.

tuned_hpo_params: Option<TunedHpoParams>

If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.

status: Option<String>

The status of the solution version.

A solution version can be in one of the following states:

  • CREATE PENDING

  • CREATE IN_PROGRESS

  • ACTIVE

  • CREATE FAILED

  • CREATE STOPPING

  • CREATE STOPPED

failure_reason: Option<String>

If training a solution version fails, the reason for the failure.

creation_date_time: Option<DateTime>

The date and time (in Unix time) that this version of the solution was created.

last_updated_date_time: Option<DateTime>

The date and time (in Unix time) that the solution was last updated.

Implementations

The ARN of the solution version.

The ARN of the solution.

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.

When true, Amazon Personalize searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses recipeArn.

The ARN of the recipe used in the solution.

The event type (for example, 'click' or 'like') that is used for training the model.

The Amazon Resource Name (ARN) of the dataset group providing the training data.

Describes the configuration properties for the solution.

The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.

The scope of training to be performed when creating the solution version. The FULL option trains the solution version based on the entirety of the input solution's training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

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 HRNN-Coldstart recipe.

If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.

The status of the solution version.

A solution version can be in one of the following states:

  • CREATE PENDING

  • CREATE IN_PROGRESS

  • ACTIVE

  • CREATE FAILED

  • CREATE STOPPING

  • CREATE STOPPED

If training a solution version fails, the reason for the failure.

The date and time (in Unix time) that this version of the solution was created.

The date and time (in Unix time) that the solution was last updated.

Creates a new builder-style object to manufacture SolutionVersion

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