Struct aws_sdk_sagemaker::model::ContinuousParameterRange

#[non_exhaustive]
pub struct ContinuousParameterRange {
    pub name: Option<String>,
    pub min_value: Option<String>,
    pub max_value: Option<String>,
    pub scaling_type: Option<HyperParameterScalingType>,
}

A list of continuous hyperparameters to tune.

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 continuous hyperparameter to tune.

min_value: Option<String>

The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.

max_value: Option<String>

The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.

scaling_type: Option<HyperParameterScalingType>

The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:

Auto

Amazon SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.

Linear

Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.

Logarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.

Logarithmic scaling works only for ranges that have only values greater than 0.

ReverseLogarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.

Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.

Implementations

impl ContinuousParameterRange

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

The name of the continuous hyperparameter to tune.

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

The minimum value for the hyperparameter. The tuning job uses floating-point values between this value and MaxValuefor tuning.

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

The maximum value for the hyperparameter. The tuning job uses floating-point values between MinValue value and this value for tuning.

pub fn scaling_type(&self) -> Option<&HyperParameterScalingType>

The scale that hyperparameter tuning uses to search the hyperparameter range. For information about choosing a hyperparameter scale, see Hyperparameter Scaling. One of the following values:

Auto

Amazon SageMaker hyperparameter tuning chooses the best scale for the hyperparameter.

Linear

Hyperparameter tuning searches the values in the hyperparameter range by using a linear scale.

Logarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a logarithmic scale.

Logarithmic scaling works only for ranges that have only values greater than 0.

ReverseLogarithmic

Hyperparameter tuning searches the values in the hyperparameter range by using a reverse logarithmic scale.

Reverse logarithmic scaling works only for ranges that are entirely within the range 0<=x<1.0.

impl ContinuousParameterRange

pub fn builder() -> Builder

Creates a new builder-style object to manufacture ContinuousParameterRange

Trait Implementations

impl Clone for ContinuousParameterRange

fn clone(&self) -> ContinuousParameterRange

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for ContinuousParameterRange

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

Formats the value using the given formatter.

impl PartialEq<ContinuousParameterRange> for ContinuousParameterRange

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

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

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

This method tests for !=.

impl StructuralPartialEq for ContinuousParameterRange