Struct aws_sdk_personalize::model::Algorithm [−][src]
#[non_exhaustive]pub struct Algorithm {
pub name: Option<String>,
pub algorithm_arn: Option<String>,
pub algorithm_image: Option<AlgorithmImage>,
pub default_hyper_parameters: Option<HashMap<String, String>>,
pub default_hyper_parameter_ranges: Option<DefaultHyperParameterRanges>,
pub default_resource_config: Option<HashMap<String, String>>,
pub training_input_mode: Option<String>,
pub role_arn: Option<String>,
pub creation_date_time: Option<DateTime>,
pub last_updated_date_time: Option<DateTime>,
}Expand description
Describes a custom algorithm.
Fields (Non-exhaustive)
This struct is marked as non-exhaustive
Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.name: Option<String>The name of the algorithm.
algorithm_arn: Option<String>The Amazon Resource Name (ARN) of the algorithm.
algorithm_image: Option<AlgorithmImage>The URI of the Docker container for the algorithm image.
default_hyper_parameters: Option<HashMap<String, String>>Specifies the default hyperparameters.
default_hyper_parameter_ranges: Option<DefaultHyperParameterRanges>Specifies the default hyperparameters, their ranges, and whether they are tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
default_resource_config: Option<HashMap<String, String>>Specifies the default maximum number of training jobs and parallel training jobs.
training_input_mode: Option<String>The training input mode.
role_arn: Option<String>The Amazon Resource Name (ARN) of the role.
creation_date_time: Option<DateTime>The date and time (in Unix time) that the algorithm was created.
last_updated_date_time: Option<DateTime>The date and time (in Unix time) that the algorithm was last updated.
Implementations
The Amazon Resource Name (ARN) of the algorithm.
The URI of the Docker container for the algorithm image.
Specifies the default hyperparameters.
Specifies the default hyperparameters, their ranges, and whether they are tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Specifies the default maximum number of training jobs and parallel training jobs.
The training input mode.
The date and time (in Unix time) that the algorithm was created.
The date and time (in Unix time) that the algorithm was last updated.
Trait Implementations
Auto Trait Implementations
impl RefUnwindSafe for Algorithm
impl UnwindSafe for Algorithm
Blanket Implementations
Mutably borrows from an owned value. Read more
Attaches the provided Subscriber to this type, returning a
WithDispatch wrapper. Read more
Attaches the current default Subscriber to this type, returning a
WithDispatch wrapper. Read more