Struct HyperParameterTuningJobConfigBuilder

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#[non_exhaustive]
pub struct HyperParameterTuningJobConfigBuilder { /* private fields */ }

Expand description

A builder for HyperParameterTuningJobConfig.

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impl HyperParameterTuningJobConfigBuilder

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pub fn strategy(self, input: HyperParameterTuningJobStrategyType) -> Self

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.

This field is required.

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pub fn set_strategy( self, input: Option<HyperParameterTuningJobStrategyType>, ) -> Self

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.

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pub fn get_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.

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pub fn strategy_config( self, input: HyperParameterTuningJobStrategyConfig, ) -> Self

The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.

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pub fn set_strategy_config( self, input: Option<HyperParameterTuningJobStrategyConfig>, ) -> Self

The configuration for the Hyperband optimization strategy. This parameter should be provided only if Hyperband is selected as the strategy for HyperParameterTuningJobConfig.

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pub fn get_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.

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pub fn hyper_parameter_tuning_job_objective( self, input: HyperParameterTuningJobObjective, ) -> Self

The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

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pub fn set_hyper_parameter_tuning_job_objective( self, input: Option<HyperParameterTuningJobObjective>, ) -> Self

The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

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pub fn get_hyper_parameter_tuning_job_objective( &self, ) -> &Option<HyperParameterTuningJobObjective>

The HyperParameterTuningJobObjective specifies the objective metric used to evaluate the performance of training jobs launched by this tuning job.

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pub fn resource_limits(self, input: ResourceLimits) -> Self

The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

This field is required.

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pub fn set_resource_limits(self, input: Option<ResourceLimits>) -> Self

The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

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

The ResourceLimits object that specifies the maximum number of training and parallel training jobs that can be used for this hyperparameter tuning job.

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pub fn parameter_ranges(self, input: ParameterRanges) -> Self

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

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pub fn set_parameter_ranges(self, input: Option<ParameterRanges>) -> Self

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

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pub fn get_parameter_ranges(&self) -> &Option<ParameterRanges>

The ParameterRanges object that specifies the ranges of hyperparameters that this tuning job searches over to find the optimal configuration for the highest model performance against your chosen objective metric.

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pub fn training_job_early_stopping_type( self, input: TrainingJobEarlyStoppingType, ) -> Self

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.

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pub fn set_training_job_early_stopping_type( self, input: Option<TrainingJobEarlyStoppingType>, ) -> Self

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.

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pub fn get_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.

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pub fn tuning_job_completion_criteria( self, input: TuningJobCompletionCriteria, ) -> Self

The tuning job's completion criteria.

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pub fn set_tuning_job_completion_criteria( self, input: Option<TuningJobCompletionCriteria>, ) -> Self

The tuning job's completion criteria.

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pub fn get_tuning_job_completion_criteria( &self, ) -> &Option<TuningJobCompletionCriteria>

The tuning job's completion criteria.

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pub fn random_seed(self, input: i32) -> Self

A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.

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pub fn set_random_seed(self, input: Option<i32>) -> Self

A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.

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pub fn get_random_seed(&self) -> &Option<i32>

A value used to initialize a pseudo-random number generator. Setting a random seed and using the same seed later for the same tuning job will allow hyperparameter optimization to find more a consistent hyperparameter configuration between the two runs.

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pub fn build(self) -> HyperParameterTuningJobConfig

Consumes the builder and constructs a HyperParameterTuningJobConfig.

Trait Implementations§

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impl Clone for HyperParameterTuningJobConfigBuilder

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fn clone(&self) -> HyperParameterTuningJobConfigBuilder

Returns a duplicate of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for HyperParameterTuningJobConfigBuilder

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

Formats the value using the given formatter. Read more

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impl Default for HyperParameterTuningJobConfigBuilder

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fn default() -> HyperParameterTuningJobConfigBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for HyperParameterTuningJobConfigBuilder

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

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

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

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

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impl StructuralPartialEq for HyperParameterTuningJobConfigBuilder

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impl UnwindSafe for HyperParameterTuningJobConfigBuilder

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Struct HyperParameterTuningJobConfigBuilderCopy item path

Implementations§

impl HyperParameterTuningJobConfigBuilder

pub fn strategy(self, input: HyperParameterTuningJobStrategyType) -> Self

pub fn set_strategy( self, input: Option<HyperParameterTuningJobStrategyType>, ) -> Self

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

pub fn strategy_config( self, input: HyperParameterTuningJobStrategyConfig, ) -> Self

pub fn set_strategy_config( self, input: Option<HyperParameterTuningJobStrategyConfig>, ) -> Self

pub fn get_strategy_config( &self, ) -> &Option<HyperParameterTuningJobStrategyConfig>

pub fn hyper_parameter_tuning_job_objective( self, input: HyperParameterTuningJobObjective, ) -> Self

pub fn set_hyper_parameter_tuning_job_objective( self, input: Option<HyperParameterTuningJobObjective>, ) -> Self

pub fn get_hyper_parameter_tuning_job_objective( &self, ) -> &Option<HyperParameterTuningJobObjective>

pub fn resource_limits(self, input: ResourceLimits) -> Self

pub fn set_resource_limits(self, input: Option<ResourceLimits>) -> Self

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

pub fn parameter_ranges(self, input: ParameterRanges) -> Self

pub fn set_parameter_ranges(self, input: Option<ParameterRanges>) -> Self

pub fn get_parameter_ranges(&self) -> &Option<ParameterRanges>

pub fn training_job_early_stopping_type( self, input: TrainingJobEarlyStoppingType, ) -> Self

pub fn set_training_job_early_stopping_type( self, input: Option<TrainingJobEarlyStoppingType>, ) -> Self

pub fn get_training_job_early_stopping_type( &self, ) -> &Option<TrainingJobEarlyStoppingType>

pub fn tuning_job_completion_criteria( self, input: TuningJobCompletionCriteria, ) -> Self

pub fn set_tuning_job_completion_criteria( self, input: Option<TuningJobCompletionCriteria>, ) -> Self

pub fn get_tuning_job_completion_criteria( &self, ) -> &Option<TuningJobCompletionCriteria>

pub fn random_seed(self, input: i32) -> Self

pub fn set_random_seed(self, input: Option<i32>) -> Self

pub fn get_random_seed(&self) -> &Option<i32>

pub fn build(self) -> HyperParameterTuningJobConfig

Trait Implementations§

impl Clone for HyperParameterTuningJobConfigBuilder

fn clone(&self) -> HyperParameterTuningJobConfigBuilder

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

impl Debug for HyperParameterTuningJobConfigBuilder

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

impl Default for HyperParameterTuningJobConfigBuilder

fn default() -> HyperParameterTuningJobConfigBuilder

impl PartialEq for HyperParameterTuningJobConfigBuilder

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

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

impl StructuralPartialEq for HyperParameterTuningJobConfigBuilder

Auto Trait Implementations§

impl Freeze for HyperParameterTuningJobConfigBuilder

impl RefUnwindSafe for HyperParameterTuningJobConfigBuilder

impl Send for HyperParameterTuningJobConfigBuilder

impl Sync for HyperParameterTuningJobConfigBuilder

impl Unpin for HyperParameterTuningJobConfigBuilder

impl UnwindSafe for HyperParameterTuningJobConfigBuilder

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fn into(self) -> U

impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unsharedwhere Shared: FromUnshared<Unshared>,

fn into_shared(self) -> Shared

impl<T> Paint for Twhere T: ?Sized,

fn fg(&self, value: Color) -> Painted<&T>

§Example

fn primary(&self) -> Painted<&T>

§Example

fn fixed(&self, color: u8) -> Painted<&T>

§Example

fn rgb(&self, r: u8, g: u8, b: u8) -> Painted<&T>

§Example

fn black(&self) -> Painted<&T>

§Example

fn red(&self) -> Painted<&T>

Struct HyperParameterTuningJobConfigBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,