Struct aws_sdk_sagemaker::model::HyperParameterTuningJobSummary

#[non_exhaustive]
pub struct HyperParameterTuningJobSummary {
    pub hyper_parameter_tuning_job_name: Option<String>,
    pub hyper_parameter_tuning_job_arn: Option<String>,
    pub hyper_parameter_tuning_job_status: Option<HyperParameterTuningJobStatus>,
    pub strategy: Option<HyperParameterTuningJobStrategyType>,
    pub creation_time: Option<DateTime>,
    pub hyper_parameter_tuning_end_time: Option<DateTime>,
    pub last_modified_time: Option<DateTime>,
    pub training_job_status_counters: Option<TrainingJobStatusCounters>,
    pub objective_status_counters: Option<ObjectiveStatusCounters>,
    pub resource_limits: Option<ResourceLimits>,
}

Provides summary information about a hyperparameter tuning job.

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.

hyper_parameter_tuning_job_name: Option<String>

The name of the tuning job.

hyper_parameter_tuning_job_arn: Option<String>

The Amazon Resource Name (ARN) of the tuning job.

hyper_parameter_tuning_job_status: Option<HyperParameterTuningJobStatus>

The status of the tuning job.

strategy: Option<HyperParameterTuningJobStrategyType>

Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to use for each iteration. Currently, the only valid value is Bayesian.

creation_time: Option<DateTime>

The date and time that the tuning job was created.

hyper_parameter_tuning_end_time: Option<DateTime>

The date and time that the tuning job ended.

last_modified_time: Option<DateTime>

The date and time that the tuning job was modified.

training_job_status_counters: Option<TrainingJobStatusCounters>

The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.

objective_status_counters: Option<ObjectiveStatusCounters>

The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.

resource_limits: Option<ResourceLimits>

The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.

Implementations

impl HyperParameterTuningJobSummary

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

The name of the tuning job.

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

The Amazon Resource Name (ARN) of the tuning job.

pub fn hyper_parameter_tuning_job_status(
    &self
) -> Option<&HyperParameterTuningJobStatus>

The status of the tuning job.

pub fn strategy(&self) -> Option<&HyperParameterTuningJobStrategyType>

Specifies the search strategy hyperparameter tuning uses to choose which hyperparameters to use for each iteration. Currently, the only valid value is Bayesian.

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

The date and time that the tuning job was created.

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

The date and time that the tuning job ended.

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

The date and time that the tuning job was modified.

pub fn training_job_status_counters(&self) -> Option<&TrainingJobStatusCounters>

The TrainingJobStatusCounters object that specifies the numbers of training jobs, categorized by status, that this tuning job launched.

pub fn objective_status_counters(&self) -> Option<&ObjectiveStatusCounters>

The ObjectiveStatusCounters object that specifies the numbers of training jobs, categorized by objective metric status, that this tuning job launched.

pub fn resource_limits(&self) -> Option<&ResourceLimits>

The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs allowed for this tuning job.

impl HyperParameterTuningJobSummary

pub fn builder() -> Builder

Creates a new builder-style object to manufacture HyperParameterTuningJobSummary

Trait Implementations

impl Clone for HyperParameterTuningJobSummary

fn clone(&self) -> HyperParameterTuningJobSummary

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for HyperParameterTuningJobSummary

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

Formats the value using the given formatter.

impl PartialEq<HyperParameterTuningJobSummary> for HyperParameterTuningJobSummary

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

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

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

This method tests for !=.

impl StructuralPartialEq for HyperParameterTuningJobSummary