Struct ActiveLearningConfig 

#[non_exhaustive]
pub struct ActiveLearningConfig {
    pub sample_config: Option<SampleConfig>,
    pub training_config: Option<TrainingConfig>,
    pub human_labeling_budget: Option<HumanLabelingBudget>,
    /* private fields */
}

Available on crate feature job-service only.

Parameters that configure the active learning pipeline. Active learning will label the data incrementally by several iterations. For every iteration, it will select a batch of data based on the sampling strategy.

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.

sample_config: Option<SampleConfig>

Active learning data sampling config. For every active learning labeling iteration, it will select a batch of data based on the sampling strategy.

training_config: Option<TrainingConfig>

CMLE training config. For every active learning labeling iteration, system will train a machine learning model on CMLE. The trained model will be used by data sampling algorithm to select DataItems.

human_labeling_budget: Option<HumanLabelingBudget>

Required. Max human labeling DataItems. The rest part will be labeled by machine.

Implementations

impl ActiveLearningConfig

pub fn new() -> Self

pub fn set_sample_config<T>(self, v: T) -> Self

where T: Into<SampleConfig>,

Sets the value of sample_config.

Example

use google_cloud_aiplatform_v1::model::SampleConfig;
let x = ActiveLearningConfig::new().set_sample_config(SampleConfig::default()/* use setters */);

pub fn set_or_clear_sample_config<T>(self, v: Option<T>) -> Self

where T: Into<SampleConfig>,

Sets or clears the value of sample_config.

Example

use google_cloud_aiplatform_v1::model::SampleConfig;
let x = ActiveLearningConfig::new().set_or_clear_sample_config(Some(SampleConfig::default()/* use setters */));
let x = ActiveLearningConfig::new().set_or_clear_sample_config(None::<SampleConfig>);

pub fn set_training_config<T>(self, v: T) -> Self

where T: Into<TrainingConfig>,

Sets the value of training_config.

Example

use google_cloud_aiplatform_v1::model::TrainingConfig;
let x = ActiveLearningConfig::new().set_training_config(TrainingConfig::default()/* use setters */);

pub fn set_or_clear_training_config<T>(self, v: Option<T>) -> Self

where T: Into<TrainingConfig>,

Sets or clears the value of training_config.

Example

use google_cloud_aiplatform_v1::model::TrainingConfig;
let x = ActiveLearningConfig::new().set_or_clear_training_config(Some(TrainingConfig::default()/* use setters */));
let x = ActiveLearningConfig::new().set_or_clear_training_config(None::<TrainingConfig>);

pub fn set_human_labeling_budget<T: Into<Option<HumanLabelingBudget>>>( self, v: T, ) -> Self

Sets the value of human_labeling_budget.

Note that all the setters affecting human_labeling_budget are mutually exclusive.

Example

use google_cloud_aiplatform_v1::model::active_learning_config::HumanLabelingBudget;
let x = ActiveLearningConfig::new().set_human_labeling_budget(Some(HumanLabelingBudget::MaxDataItemCount(42)));

pub fn max_data_item_count(&self) -> Option<&i64>

The value of human_labeling_budget if it holds a MaxDataItemCount, None if the field is not set or holds a different branch.

pub fn set_max_data_item_count<T: Into<i64>>(self, v: T) -> Self

Sets the value of human_labeling_budget to hold a MaxDataItemCount.

Note that all the setters affecting human_labeling_budget are mutually exclusive.

Example

let x = ActiveLearningConfig::new().set_max_data_item_count(42);
assert!(x.max_data_item_count().is_some());
assert!(x.max_data_item_percentage().is_none());

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

The value of human_labeling_budget if it holds a MaxDataItemPercentage, None if the field is not set or holds a different branch.

pub fn set_max_data_item_percentage<T: Into<i32>>(self, v: T) -> Self

Sets the value of human_labeling_budget to hold a MaxDataItemPercentage.

Note that all the setters affecting human_labeling_budget are mutually exclusive.

Example

let x = ActiveLearningConfig::new().set_max_data_item_percentage(42);
assert!(x.max_data_item_percentage().is_some());
assert!(x.max_data_item_count().is_none());

Trait Implementations

impl Clone for ActiveLearningConfig

fn clone(&self) -> ActiveLearningConfig

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ActiveLearningConfig

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

Formats the value using the given formatter.

impl Default for ActiveLearningConfig

fn default() -> ActiveLearningConfig

Returns the “default value” for a type.

impl Message for ActiveLearningConfig

fn typename() -> &'static str

The typename of this message.

impl PartialEq for ActiveLearningConfig

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

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

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 ActiveLearningConfig