#[non_exhaustive]pub struct HyperParameterTuningJobConfig { /* private fields */ }Expand description
Configures a hyperparameter tuning job.
Implementations
sourceimpl HyperParameterTuningJobConfig
impl HyperParameterTuningJobConfig
sourcepub fn strategy(&self) -> Option<&HyperParameterTuningJobStrategyType>
pub fn strategy(&self) -> Option<&HyperParameterTuningJobStrategyType>
Specifies how hyperparameter tuning chooses the combinations of hyperparameter values to use for the training job it launches. For information about search strategies, see How Hyperparameter Tuning Works.
sourcepub fn strategy_config(&self) -> Option<&HyperParameterTuningJobStrategyConfig>
pub fn strategy_config(&self) -> Option<&HyperParameterTuningJobStrategyConfig>
The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.
sourcepub fn hyper_parameter_tuning_job_objective(
&self
) -> Option<&HyperParameterTuningJobObjective>
pub fn hyper_parameter_tuning_job_objective(
&self
) -> Option<&HyperParameterTuningJobObjective>
The HyperParameterTuningJobObjective object that specifies the objective metric for this tuning job.
sourcepub fn resource_limits(&self) -> Option<&ResourceLimits>
pub fn resource_limits(&self) -> Option<&ResourceLimits>
The ResourceLimits object that specifies the maximum number of training jobs and parallel training jobs for this tuning job.
sourcepub fn parameter_ranges(&self) -> Option<&ParameterRanges>
pub fn parameter_ranges(&self) -> Option<&ParameterRanges>
The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches.
sourcepub fn training_job_early_stopping_type(
&self
) -> Option<&TrainingJobEarlyStoppingType>
pub fn training_job_early_stopping_type(
&self
) -> Option<&TrainingJobEarlyStoppingType>
Specifies whether to use early stopping for training jobs launched by the hyperparameter tuning job. Because the Hyperband strategy has its own advanced internal early stopping mechanism, TrainingJobEarlyStoppingType must be OFF to use Hyperband. This parameter can take on one of the following values (the default value is OFF):
- OFF
-
Training jobs launched by the hyperparameter tuning job do not use early stopping.
- AUTO
-
SageMaker stops training jobs launched by the hyperparameter tuning job when they are unlikely to perform better than previously completed training jobs. For more information, see Stop Training Jobs Early.
sourcepub fn tuning_job_completion_criteria(
&self
) -> Option<&TuningJobCompletionCriteria>
pub fn tuning_job_completion_criteria(
&self
) -> Option<&TuningJobCompletionCriteria>
The tuning job's completion criteria.
sourceimpl HyperParameterTuningJobConfig
impl HyperParameterTuningJobConfig
sourcepub fn builder() -> Builder
pub fn builder() -> Builder
Creates a new builder-style object to manufacture HyperParameterTuningJobConfig.
Trait Implementations
sourceimpl Clone for HyperParameterTuningJobConfig
impl Clone for HyperParameterTuningJobConfig
sourcefn clone(&self) -> HyperParameterTuningJobConfig
fn clone(&self) -> HyperParameterTuningJobConfig
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read more