Struct gapi_grpc::google::cloud::aiplatform::v1::ActiveLearningConfig [−][src]
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
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.
Trait Implementations
impl Clone for ActiveLearningConfig
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impl Debug for ActiveLearningConfig
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impl Default for ActiveLearningConfig
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impl Message for ActiveLearningConfig
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impl PartialEq<ActiveLearningConfig> for ActiveLearningConfig
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impl StructuralPartialEq for ActiveLearningConfig
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Auto Trait Implementations
impl RefUnwindSafe for ActiveLearningConfig
impl Send for ActiveLearningConfig
impl Sync for ActiveLearningConfig
impl Unpin for ActiveLearningConfig
impl UnwindSafe for ActiveLearningConfig
Blanket Implementations
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> Borrow<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
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T: ?Sized,
impl<T> From<T> for T
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impl<T> Instrument for T
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impl<T> Instrument for T
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impl<T, U> Into<U> for T where
U: From<T>,
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U: From<T>,
impl<T> IntoRequest<T> for T
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impl<T> ToOwned for T where
T: Clone,
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T: Clone,
impl<T, U> TryFrom<U> for T where
U: Into<T>,
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U: Into<T>,
impl<T, U> TryInto<U> for T where
U: TryFrom<T>,
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U: TryFrom<T>,
impl<V, T> VZip<V> for T where
V: MultiLane<T>,
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V: MultiLane<T>,