Struct Algorithm

#[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>,
}

Describes a custom algorithm.

Fields (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.

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

impl Algorithm

pub fn name(&self) -> Option<&str>

The name of the algorithm.

pub fn algorithm_arn(&self) -> Option<&str>

The Amazon Resource Name (ARN) of the algorithm.

pub fn algorithm_image(&self) -> Option<&AlgorithmImage>

The URI of the Docker container for the algorithm image.

pub fn default_hyper_parameters(&self) -> Option<&HashMap<String, String>>

Specifies the default hyperparameters.

pub fn default_hyper_parameter_ranges( &self, ) -> 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).

pub fn default_resource_config(&self) -> Option<&HashMap<String, String>>

Specifies the default maximum number of training jobs and parallel training jobs.

pub fn training_input_mode(&self) -> Option<&str>

The training input mode.

pub fn role_arn(&self) -> Option<&str>

The Amazon Resource Name (ARN) of the role.

pub fn creation_date_time(&self) -> Option<&DateTime>

The date and time (in Unix time) that the algorithm was created.

pub fn last_updated_date_time(&self) -> Option<&DateTime>

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

impl Algorithm

pub fn builder() -> AlgorithmBuilder

Creates a new builder-style object to manufacture Algorithm.

Trait Implementations

impl Clone for Algorithm

fn clone(&self) -> Algorithm

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Algorithm

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

Formats the value using the given formatter.

impl PartialEq for Algorithm

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

Tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for Algorithm